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msmarco_v2.1_doc_01_1668156367#6_2446069291 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| A positive relationship (also called positive correlation) – that means if the independent variable increases, then the dependent variable would also increase and vice versa. The above example about the kids’ age and height is a classical positive relationship. A negative relationship (negative correlation) – when the independent variable increases and the dependent variable decrease and vice versa. Example: when the car age increases, the car price decreases. So, we use bivariate data to compare two sets of data and to discover any relationships between them. Bivariate Data Analysis
Bivariate analysis allows you to study the relationship between 2 variables and has many practical uses in the real life. It aims to find out whether there exists an association between the variables and what is its strength. Bivariate analysis also allows you to test a hypothesis of association and causality. It also helps you to predict the values of a dependent variable based on the changes of an independent variable. | 2,049 | 3,065 |
msmarco_v2.1_doc_01_1668156367#7_2446070735 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| So, we use bivariate data to compare two sets of data and to discover any relationships between them. Bivariate Data Analysis
Bivariate analysis allows you to study the relationship between 2 variables and has many practical uses in the real life. It aims to find out whether there exists an association between the variables and what is its strength. Bivariate analysis also allows you to test a hypothesis of association and causality. It also helps you to predict the values of a dependent variable based on the changes of an independent variable. Let’s see how the bivariate data work with linear regression models. Example 2: Let’s say you have to study the relationship between the age and the systolic blood pressure in a company. You have a sample of 10 workers aged thirty to fifty-five years. The results are presented in the following bivariate data table. | 2,514 | 3,382 |
msmarco_v2.1_doc_01_1668156367#8_2446072026 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| Let’s see how the bivariate data work with linear regression models. Example 2: Let’s say you have to study the relationship between the age and the systolic blood pressure in a company. You have a sample of 10 workers aged thirty to fifty-five years. The results are presented in the following bivariate data table. Employee
Age
Systolic Blood Pressure
1
37
130
2
38
140
3
40
132
4
42
149
5
45
144
6
48
157
7
50
161
8
52
145
9
53
165
10
55
162
Now, we need to display this table graphically to be able to make some conclusions. Bivariate data is most often displayed using a scatter plot. This is a plot on a grid paper of y (y-axis) against x (x-axis) and indicates the behavior of given data sets. Scatter plot is one of the popular types of graphs that give us a much more clear picture of a possible relationship between the variables. Let’s build our Scatter Plot based on the table above: | 3,065 | 3,961 |
msmarco_v2.1_doc_01_1668156367#9_2446073382 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| Employee
Age
Systolic Blood Pressure
1
37
130
2
38
140
3
40
132
4
42
149
5
45
144
6
48
157
7
50
161
8
52
145
9
53
165
10
55
162
Now, we need to display this table graphically to be able to make some conclusions. Bivariate data is most often displayed using a scatter plot. This is a plot on a grid paper of y (y-axis) against x (x-axis) and indicates the behavior of given data sets. Scatter plot is one of the popular types of graphs that give us a much more clear picture of a possible relationship between the variables. Let’s build our Scatter Plot based on the table above: The above scatter plot illustrates that the values seem to group around a straight line i.e it shows that there is a possible linear relationship between the age and systolic blood pressure. You can create scatter plots very easily with a variety of free graphing software available online. What does this graph show us? It is obvious that there is a relationship between age and blood pressure and moreover this relationship is positive (i.e. we have positive correlation). The older the age, the higher the systolic blood pressure. | 3,382 | 4,495 |
msmarco_v2.1_doc_01_1668156367#10_2446074945 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| The above scatter plot illustrates that the values seem to group around a straight line i.e it shows that there is a possible linear relationship between the age and systolic blood pressure. You can create scatter plots very easily with a variety of free graphing software available online. What does this graph show us? It is obvious that there is a relationship between age and blood pressure and moreover this relationship is positive (i.e. we have positive correlation). The older the age, the higher the systolic blood pressure. The line that you see in the graph is called “line of best fit” (or the regression line). The line of best fit aims to answer the question whether these two variables correlate. It can be used to help you determine trends within the data sets. Furthermore, the line of best fit illustrates the strength of the correlation. We have strong correlation when there is little space between the data points and the line. | 3,961 | 4,910 |
msmarco_v2.1_doc_01_1668156367#11_2446076317 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| The line that you see in the graph is called “line of best fit” (or the regression line). The line of best fit aims to answer the question whether these two variables correlate. It can be used to help you determine trends within the data sets. Furthermore, the line of best fit illustrates the strength of the correlation. We have strong correlation when there is little space between the data points and the line. In our example above, we have a strong correlation. If the data points are spread quite far away from the line of best fit, we say we have a weak correlation. More on scatter plots you can find in our post “ what does a scatter plot show “. Let’s investigate further. We constated that in our example, there is a positive and strong linear relationship between age and blood pressure. | 4,495 | 5,295 |
msmarco_v2.1_doc_01_1668156367#12_2446077555 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| In our example above, we have a strong correlation. If the data points are spread quite far away from the line of best fit, we say we have a weak correlation. More on scatter plots you can find in our post “ what does a scatter plot show “. Let’s investigate further. We constated that in our example, there is a positive and strong linear relationship between age and blood pressure. However, how strong is that relationship? What is its strength? This is where the correlation coefficient comes to answer this question. The correlation coefficient (R) is a numerical value measured between -1 and 1. It indicates the strength of the linear relationship between two given variables. | 4,911 | 5,594 |
msmarco_v2.1_doc_01_1668156367#13_2446078667 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| However, how strong is that relationship? What is its strength? This is where the correlation coefficient comes to answer this question. The correlation coefficient (R) is a numerical value measured between -1 and 1. It indicates the strength of the linear relationship between two given variables. For describing a linear regression, the coefficient is called Pearson’s correlation coefficient. When the correlation coefficient is closer to 1 it shows a strong positive relationship. When it is close to -1, there is a strong negative relationship. A value of 0 tells us that there is no relationship. We need to calculate our correlation coefficient between age and blood pressure. | 5,296 | 5,979 |
msmarco_v2.1_doc_01_1668156367#14_2446079769 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| For describing a linear regression, the coefficient is called Pearson’s correlation coefficient. When the correlation coefficient is closer to 1 it shows a strong positive relationship. When it is close to -1, there is a strong negative relationship. A value of 0 tells us that there is no relationship. We need to calculate our correlation coefficient between age and blood pressure. There is a long formula (for Pearson’s correlation coefficient) for this but you don’t need to remember it. All you need to do is to use a free or premium calculator such as those on www.socscistatistics.com . When we put our bivariate data on this calculator we got the following result: R = 0.8435
The value of the correlation coefficient (R) is 0.8435. It shows a strong positive correlation. | 5,595 | 6,375 |
msmarco_v2.1_doc_01_1668156367#15_2446080979 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| There is a long formula (for Pearson’s correlation coefficient) for this but you don’t need to remember it. All you need to do is to use a free or premium calculator such as those on www.socscistatistics.com . When we put our bivariate data on this calculator we got the following result: R = 0.8435
The value of the correlation coefficient (R) is 0.8435. It shows a strong positive correlation. Now, let’s calculate the equation of the regression line (the best fit line) to find out the slope of the line. For that purpose let’s remind the simple linear regression equation: Y = Β0 + Β1X
Where: X – the value of the independent variable,
Y – the value of the dependent variable. Β0 – is a constant (shows the value of Y when the value of X=0)
Β1 – the regression coefficient (shows how much Y changes for each unit change in X)
Again, we will use the same online software ( socscistatistics.com) to calculate the linear regression equation. | 5,980 | 6,922 |
msmarco_v2.1_doc_01_1668156367#16_2446082400 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| Now, let’s calculate the equation of the regression line (the best fit line) to find out the slope of the line. For that purpose let’s remind the simple linear regression equation: Y = Β0 + Β1X
Where: X – the value of the independent variable,
Y – the value of the dependent variable. Β0 – is a constant (shows the value of Y when the value of X=0)
Β1 – the regression coefficient (shows how much Y changes for each unit change in X)
Again, we will use the same online software ( socscistatistics.com) to calculate the linear regression equation. The result is: Y = 1.612*X + 74.35
More on linear regression equation and explanation, you can see in our post for linear regression examples. So, from the above bivariate data analysis example that includes workers of the company, we can say that blood pressure increased as the age increased. This indicates that age is a significant factor that influences the change of blood pressure. Other popular positive bivariate data correlation examples are: | 6,375 | 7,375 |
msmarco_v2.1_doc_01_1668156367#17_2446083868 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| The result is: Y = 1.612*X + 74.35
More on linear regression equation and explanation, you can see in our post for linear regression examples. So, from the above bivariate data analysis example that includes workers of the company, we can say that blood pressure increased as the age increased. This indicates that age is a significant factor that influences the change of blood pressure. Other popular positive bivariate data correlation examples are: temperature and the amount of the ice cream sales, alcohol consumption and cholesterol levels, weights and heights of college students, and etc. Let’s see bivariate data analysis examples for a negative correlation. Example 3: The below bivariate data table shows the number of student absences and their final grades in a class. Student
Number of Absences
Final Grades
1
0
90
2
1
85
3
1
88
4
2
84
5
3
82
6
3
80
7
4
75
8
5
60
9
6
72
10
7
64
It is quite obvious that these two variables have a negative correlation between them. | 6,923 | 7,903 |
msmarco_v2.1_doc_01_1668156367#18_2446085301 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| temperature and the amount of the ice cream sales, alcohol consumption and cholesterol levels, weights and heights of college students, and etc. Let’s see bivariate data analysis examples for a negative correlation. Example 3: The below bivariate data table shows the number of student absences and their final grades in a class. Student
Number of Absences
Final Grades
1
0
90
2
1
85
3
1
88
4
2
84
5
3
82
6
3
80
7
4
75
8
5
60
9
6
72
10
7
64
It is quite obvious that these two variables have a negative correlation between them. When the number of student absences increases, the final grades decrease. Now, let’s plot the bivariate data from the table on a scatter plot and to create the best-fit line: Note how the regression line looks – it has a downward slope. This downward slope indicates there is a negative linear association. We can calculate the correlation coefficient and linear regression equation. | 7,376 | 8,287 |
msmarco_v2.1_doc_01_1668156367#19_2446086674 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| When the number of student absences increases, the final grades decrease. Now, let’s plot the bivariate data from the table on a scatter plot and to create the best-fit line: Note how the regression line looks – it has a downward slope. This downward slope indicates there is a negative linear association. We can calculate the correlation coefficient and linear regression equation. Here are the results: The value of the correlation coefficient (R) is -0.9061. This is a strong negative correlation. The linear regression equation is Y = -3.971*X + 90.71. We can conclude that the least number of lessons the students skip, the higher grade could be reached. | 7,903 | 8,564 |
msmarco_v2.1_doc_01_1668156367#20_2446087758 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| Here are the results: The value of the correlation coefficient (R) is -0.9061. This is a strong negative correlation. The linear regression equation is Y = -3.971*X + 90.71. We can conclude that the least number of lessons the students skip, the higher grade could be reached. Conclusion: The above bivariate data examples aim to help you understand better how does the bivariate analysis work. Analyzing two variables is a common part of the inferential statistics types and calculations. Many business and scientific investigations include only two continuous variables. The main questions that bivariate analysis has to answer are: | 8,288 | 8,922 |
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| Conclusion: The above bivariate data examples aim to help you understand better how does the bivariate analysis work. Analyzing two variables is a common part of the inferential statistics types and calculations. Many business and scientific investigations include only two continuous variables. The main questions that bivariate analysis has to answer are: Is there a correlation between 2 given variables? Is the relationship positive or negative? What is the degree of the correlation? Is it strong or weak? Sometimes it is very logical to conclude that there is a causal link between 2 variables such as kid’s age and hight. | 8,564 | 9,193 |
msmarco_v2.1_doc_01_1668156367#22_2446089853 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| Is there a correlation between 2 given variables? Is the relationship positive or negative? What is the degree of the correlation? Is it strong or weak? Sometimes it is very logical to conclude that there is a causal link between 2 variables such as kid’s age and hight. However, is there a link between childhood obesity and incomes for families? This is where bivariate analysis can shine. If you need other practical examples in the area of management and analysis, our posts Venn diagram examples and decision tree examples might be helpful for you. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. | 8,922 | 9,797 |
msmarco_v2.1_doc_01_1668156367#23_2446091148 | http://intellspot.com/bivariate-data-examples/ | Bivariate Data Analysis: Examples, Definition, Data Sets Correlation | Bivariate Data: Examples, Definition and Analysis
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| However, is there a link between childhood obesity and incomes for families? This is where bivariate analysis can shine. If you need other practical examples in the area of management and analysis, our posts Venn diagram examples and decision tree examples might be helpful for you. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. Leave a Reply
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This site uses Akismet to reduce spam. Learn how your comment data is processed. | 9,193 | 9,905 |
msmarco_v2.1_doc_01_1668166957#0_2446092277 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| Box and Whisker Plot Examples: Real-World Problems and Answers
Box and Whisker Plot Examples
When it comes to visualizing a summary of a large data in 5 numbers, many real-world box and whisker plot examples can show you how to solve box plots. As many other graphs and diagrams in statistics, box and whisker plot is widely used for solving data problems. Believe it or not, interpreting and reading box plots can be a piece of cake. On this page: What is box and whisker plot? Definition, explanation, and analysis. Easy real-life example: problems with answers and interpretation. Comparative double box and whisker plot example: | 0 | 632 |
msmarco_v2.1_doc_01_1668166957#1_2446093280 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| What is box and whisker plot? Definition, explanation, and analysis. Easy real-life example: problems with answers and interpretation. Comparative double box and whisker plot example: to see how to compare two data sets with analysis and interpretation. Let’s define it: A box and whisker plot (also known as a box plot) is a graph that represents visually data from a five-number summary. These numbers are median, upper and lower quartile, minimum and maximum data value (extremes). Don’t panic, these numbers are easy to understand. | 448 | 984 |
msmarco_v2.1_doc_01_1668166957#2_2446094196 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| to see how to compare two data sets with analysis and interpretation. Let’s define it: A box and whisker plot (also known as a box plot) is a graph that represents visually data from a five-number summary. These numbers are median, upper and lower quartile, minimum and maximum data value (extremes). Don’t panic, these numbers are easy to understand. Look at the following example of box and whisker plot: So, there are a couple of things, you should know in order to work with box plots: Lower Extreme – the smallest value in a given dataset. Upper Extreme – the highest value in a given dataset. Median value – the middle number in the set. | 633 | 1,276 |
msmarco_v2.1_doc_01_1668166957#3_2446095236 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| Look at the following example of box and whisker plot: So, there are a couple of things, you should know in order to work with box plots: Lower Extreme – the smallest value in a given dataset. Upper Extreme – the highest value in a given dataset. Median value – the middle number in the set. Lower Quartile – below that value, the lower 25% of the data are contained. Upper Quartile – above that value, the upper 25% of the data are contained. “Whiskers” – the lines that extend from the boxes. They are used to indicate variability out of the upper and lower quartiles. To put it in another way, we have 3 key points. | 985 | 1,603 |
msmarco_v2.1_doc_01_1668166957#4_2446096266 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| Lower Quartile – below that value, the lower 25% of the data are contained. Upper Quartile – above that value, the upper 25% of the data are contained. “Whiskers” – the lines that extend from the boxes. They are used to indicate variability out of the upper and lower quartiles. To put it in another way, we have 3 key points. The first is the middle point (the median). The others are the middle points of the two halves. These three points divide the data set into quarters, that we call “quartiles”. We will make the things clearer with a simple real-world example. It also illustrates the steps for solving a box and whisker plot problem. | 1,276 | 1,919 |
msmarco_v2.1_doc_01_1668166957#5_2446097316 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| The first is the middle point (the median). The others are the middle points of the two halves. These three points divide the data set into quarters, that we call “quartiles”. We will make the things clearer with a simple real-world example. It also illustrates the steps for solving a box and whisker plot problem. Example 1: a simple box and whisker plot
Suppose you have the math test results for a class of 15 students. Here are the results: 91 95 54 69 80 85 88 73 71 70 66 90 86 84 73
It is hard to say what is the middle point (the median) because the value points are not ordered. Step 1 : | 1,604 | 2,201 |
msmarco_v2.1_doc_01_1668166957#6_2446098298 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| Example 1: a simple box and whisker plot
Suppose you have the math test results for a class of 15 students. Here are the results: 91 95 54 69 80 85 88 73 71 70 66 90 86 84 73
It is hard to say what is the middle point (the median) because the value points are not ordered. Step 1 : Order the data points from least to greatest. 54 66 69 70 71 73 73 80 84 85 86 88 90 91 95
Step 2: Find the median of the data: This is an odd set of data – you have 15 data points. It means the middle point is 80 as there are 7 data points above it and 7 numbers below. | 1,919 | 2,472 |
msmarco_v2.1_doc_01_1668166957#7_2446099231 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| Order the data points from least to greatest. 54 66 69 70 71 73 73 80 84 85 86 88 90 91 95
Step 2: Find the median of the data: This is an odd set of data – you have 15 data points. It means the middle point is 80 as there are 7 data points above it and 7 numbers below. More on how to calculate median, you can see on our post descriptive statistics examples. Step 3: Find the middle points of the two halves divided by the median (find the upper and lower quartiles). Step 4: Find the extreme values. | 2,202 | 2,704 |
msmarco_v2.1_doc_01_1668166957#8_2446100112 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| More on how to calculate median, you can see on our post descriptive statistics examples. Step 3: Find the middle points of the two halves divided by the median (find the upper and lower quartiles). Step 4: Find the extreme values. This is the easiest part. You need to find the largest and smallest data values. Extreme values = 54 and 95. So, we can determine that the five-number summary for the class of students is 54, 70, 80, 88, 95. Now we are absolutely ready to draw our box and whisker plot. | 2,472 | 2,974 |
msmarco_v2.1_doc_01_1668166957#9_2446100986 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| This is the easiest part. You need to find the largest and smallest data values. Extreme values = 54 and 95. So, we can determine that the five-number summary for the class of students is 54, 70, 80, 88, 95. Now we are absolutely ready to draw our box and whisker plot. As you see, the plot is divided into four groups: a lower whisker, a lower box half, an upper box half, and an upper whisker. Each of those groups shows 25% of the data because we have an equal amount of data in each group. Interpreting the box and whisker plot results: The box and whisker plot shows that 50% of the students have scores between 70 and 88 points. | 2,704 | 3,339 |
msmarco_v2.1_doc_01_1668166957#10_2446101993 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| As you see, the plot is divided into four groups: a lower whisker, a lower box half, an upper box half, and an upper whisker. Each of those groups shows 25% of the data because we have an equal amount of data in each group. Interpreting the box and whisker plot results: The box and whisker plot shows that 50% of the students have scores between 70 and 88 points. In addition, 75% scored lower than 88 points, and 50% have test results above 80. So, if you have test results somewhere in the lower whisker, you may need to study more. It was among the simplest box and whisker plot examples just to illustrate what the plot shows. Let’s deep further and see double box and whisker plot examples that help you to compare 2 data sets. Example 2: | 2,974 | 3,719 |
msmarco_v2.1_doc_01_1668166957#11_2446103116 | http://intellspot.com/box-and-whisker-plot-examples/ | Box and Whisker Plot Examples: Real-World Problems and Answers | Box and Whisker Plot Examples
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| In addition, 75% scored lower than 88 points, and 50% have test results above 80. So, if you have test results somewhere in the lower whisker, you may need to study more. It was among the simplest box and whisker plot examples just to illustrate what the plot shows. Let’s deep further and see double box and whisker plot examples that help you to compare 2 data sets. Example 2: comparative double box and whisker plot
Suppose an IT company has two stores that sell computers. The company recorded the number of sales each store made each month. In the past 12 months, we have the following numbers of sold computers: Store 1: 350, 460, 20, 160, 580, 250, 210, 120, 200, 510, 290, 380. | 3,339 | 4,026 |
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| comparative double box and whisker plot
Suppose an IT company has two stores that sell computers. The company recorded the number of sales each store made each month. In the past 12 months, we have the following numbers of sold computers: Store 1: 350, 460, 20, 160, 580, 250, 210, 120, 200, 510, 290, 380. Store 2: 520, 180, 260, 380, 80, 500, 630, 420, 210, 70, 440, 140. In order to compare the two stores sales performance, we will make two box and whisker plots, one for Store 1 and one for Store 2. Store 1: First, we put the data points in ascending order. | 3,720 | 4,283 |
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| Store 2: 520, 180, 260, 380, 80, 500, 630, 420, 210, 70, 440, 140. In order to compare the two stores sales performance, we will make two box and whisker plots, one for Store 1 and one for Store 2. Store 1: First, we put the data points in ascending order. 20, 120, 160, 200, 210, 250, 290, 350, 380, 460, 510 580. Now, we need to find the median. However, this is an even set of data. There isn’t only one middle point. The middle in our case belongs to sixth + seventh data points e.g. 250 and 290. | 4,026 | 4,527 |
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| 20, 120, 160, 200, 210, 250, 290, 350, 380, 460, 510 580. Now, we need to find the median. However, this is an even set of data. There isn’t only one middle point. The middle in our case belongs to sixth + seventh data points e.g. 250 and 290. And the formula for the median in an even data set is: (the sum of the two middle numbers) / 2
The median is (250 + 290) / 2 = 270
Now let’s see what happens with the lower and upper quartiles in an even data set: There are six numbers below the median, namely: 20, 120, 160, 200, 210, 250. Lower quartile is the median of these six items, so
= (third + fourth data point) / 2
= (160 + 200) / 2
= 180
There are also six numbers above the median, namely: | 4,283 | 4,981 |
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| And the formula for the median in an even data set is: (the sum of the two middle numbers) / 2
The median is (250 + 290) / 2 = 270
Now let’s see what happens with the lower and upper quartiles in an even data set: There are six numbers below the median, namely: 20, 120, 160, 200, 210, 250. Lower quartile is the median of these six items, so
= (third + fourth data point) / 2
= (160 + 200) / 2
= 180
There are also six numbers above the median, namely: 290, 350, 380, 460, 510 580. Upper quartile is the median of these six data points. = (third + fourth data points) / 2
= 420
Finally, the five-number summary for Store 1’s sales is 20, 180, 270, 420, 580. Using the same calculations, we can find that the five-number summary for Store 2 is 70, 160, 320, 470, 630
Now, we are ready to draw our comparative double box and whisker plot example: Interpreting the results: | 4,527 | 5,399 |
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| 290, 350, 380, 460, 510 580. Upper quartile is the median of these six data points. = (third + fourth data points) / 2
= 420
Finally, the five-number summary for Store 1’s sales is 20, 180, 270, 420, 580. Using the same calculations, we can find that the five-number summary for Store 2 is 70, 160, 320, 470, 630
Now, we are ready to draw our comparative double box and whisker plot example: Interpreting the results: Store 2’s highest and lowest sales are both higher than Store 1’s relevant sales. In addition, Store 2’s median sales value is higher than Store 1’s. Also, Store 2’s interquartile range is larger. These results tell us that Store 2 consistently sells more computers than Store 1. How to create box and whisker plots? | 4,982 | 5,716 |
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| Store 2’s highest and lowest sales are both higher than Store 1’s relevant sales. In addition, Store 2’s median sales value is higher than Store 1’s. Also, Store 2’s interquartile range is larger. These results tell us that Store 2 consistently sells more computers than Store 1. How to create box and whisker plots? Nowadays, you have plenty of good choices. Depending on your needs, you can create them with a free graphing software such as: Plot.ly
Meta-chart.com
Or you can use powerful premium software such as: Tableau
Of course, you can draw them with Microsoft products such as: Word
Excel
PowerPoint
Finally, just use a sheet of paper or a whiteboard to draw your box plot. | 5,399 | 6,082 |
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| Nowadays, you have plenty of good choices. Depending on your needs, you can create them with a free graphing software such as: Plot.ly
Meta-chart.com
Or you can use powerful premium software such as: Tableau
Of course, you can draw them with Microsoft products such as: Word
Excel
PowerPoint
Finally, just use a sheet of paper or a whiteboard to draw your box plot. Conclusion
The above box and whisker plot examples aim to help you understand better how to solve them. Box plots are among the most used types of graphs in the business, statistics and data analysis. It is especially useful when you want to see if a distribution is skewed and whether there are potential unusual data values (outliers) in a given dataset. These plots are also widely used for comparing two data sets. A box plot is a great way of summarizing data set measured on an interval scale (see interval data examples ). | 5,716 | 6,612 |
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| Conclusion
The above box and whisker plot examples aim to help you understand better how to solve them. Box plots are among the most used types of graphs in the business, statistics and data analysis. It is especially useful when you want to see if a distribution is skewed and whether there are potential unusual data values (outliers) in a given dataset. These plots are also widely used for comparing two data sets. A box plot is a great way of summarizing data set measured on an interval scale (see interval data examples ). It has many advantages and benefits and the most important of them are: Able to handle and present a large amount of data. A visually effective method of viewing a summary. A graphical way showing outliers. Great for comparison of two or more datasets. | 6,082 | 6,865 |
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| It has many advantages and benefits and the most important of them are: Able to handle and present a large amount of data. A visually effective method of viewing a summary. A graphical way showing outliers. Great for comparison of two or more datasets. Need more graph examples? Check our post about simple linear regression examples and Venn diagram examples. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. Leave a Reply
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| Need more graph examples? Check our post about simple linear regression examples and Venn diagram examples. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. Leave a Reply
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This site uses Akismet to reduce spam. Learn how your comment data is processed. | 6,865 | 7,402 |
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| Categorical Data: Examples, Definition and Key Characteristics
Categorical Data Examples and Definition
In the field of statistics and data management, it can be given a huge list of categorical data examples and applications. Data, in scientific meaning, is a set of information gathered for a purpose. Data is typically divided into two different types: categorical (widely known as qualitative data) and numerical (quantitative). On this page you will learn: What is categorical data? Definition and key characteristics. List of 22 examples of categorical data. Categorical data vs numerical data. | 0 | 600 |
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| On this page you will learn: What is categorical data? Definition and key characteristics. List of 22 examples of categorical data. Categorical data vs numerical data. Infographic in PDF
Let’s define it: As you might guess, categorical data is data that is divided into groups or categories. These categories are based on qualitative characteristics such as gender and colors or something else that doesn’t have a number associated with it. This doesn’t mean that categorical data cannot have numerical values. In fact, categorical data often takes numerical values, but those numbers don’t have any mathematical meaning. | 432 | 1,054 |
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| Infographic in PDF
Let’s define it: As you might guess, categorical data is data that is divided into groups or categories. These categories are based on qualitative characteristics such as gender and colors or something else that doesn’t have a number associated with it. This doesn’t mean that categorical data cannot have numerical values. In fact, categorical data often takes numerical values, but those numbers don’t have any mathematical meaning. They just represent the number of items in each group. For example 12 blondes in a class. This makes it possible to do categorical data analysis and different manipulations, particularly in a spreadsheet application. There is no order to categorical values and variables. To put it in another way, they aren’t ranked from highest to lowest. | 600 | 1,395 |
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| They just represent the number of items in each group. For example 12 blondes in a class. This makes it possible to do categorical data analysis and different manipulations, particularly in a spreadsheet application. There is no order to categorical values and variables. To put it in another way, they aren’t ranked from highest to lowest. For example, there is no order to the categories of blue, brown and green eyes. How to display categorical variables graphically? Bar charts and pie charts are great tools for comparing two or more categorical values against each other. They just represent the number of things in a category. For example, if you want to display the number of workers in a company, the outcomes can be presented on a pie chart or on a bar graph. | 1,055 | 1,824 |
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| For example, there is no order to the categories of blue, brown and green eyes. How to display categorical variables graphically? Bar charts and pie charts are great tools for comparing two or more categorical values against each other. They just represent the number of things in a category. For example, if you want to display the number of workers in a company, the outcomes can be presented on a pie chart or on a bar graph. Graphical categorical data examples: Survey on “What Motivates Employees to Work Better?” Before creating a pie or bar chart, you should check if data are in counts or percentages. To make a graphical display of categorical data, it is a necessary condition. Analysis of categorical data very often includes data tables. | 1,395 | 2,145 |
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| Graphical categorical data examples: Survey on “What Motivates Employees to Work Better?” Before creating a pie or bar chart, you should check if data are in counts or percentages. To make a graphical display of categorical data, it is a necessary condition. Analysis of categorical data very often includes data tables. The values are represented as a two-way table or contingency table by counting the number of items that are into each category. Here is an example of a categorical data two-way table for a group of 50 people. The table shows the results of the groups formed by counting the hair and eye color of each person. Two-way and contingency tables are great tools for seeing how two categorical variables are related. The table represents the counts or percentages of persons who belong to a group for two or more quantitative variables. | 1,824 | 2,675 |
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| The values are represented as a two-way table or contingency table by counting the number of items that are into each category. Here is an example of a categorical data two-way table for a group of 50 people. The table shows the results of the groups formed by counting the hair and eye color of each person. Two-way and contingency tables are great tools for seeing how two categorical variables are related. The table represents the counts or percentages of persons who belong to a group for two or more quantitative variables. It makes easier to find different relationships between the data. Let’s sum the key characteristics of categorical data we learned above: Categorical data is divided into groups or categories. The categories are based on qualitative characteristics. There is no order to categorical values and variables. | 2,146 | 2,980 |
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| It makes easier to find different relationships between the data. Let’s sum the key characteristics of categorical data we learned above: Categorical data is divided into groups or categories. The categories are based on qualitative characteristics. There is no order to categorical values and variables. Categorical data can take numerical values, but those numbers don’t have any mathematical meaning. Categorical data is displayed graphically by bar charts and pie charts. When it comes to categorical data examples, it can be given a wide range of examples. In our previous post nominal vs ordinal data, we provided a lot of examples of nominal variables (nominal data is the main type of categorical data). Examples of categorical data: | 2,676 | 3,417 |
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| Categorical data can take numerical values, but those numbers don’t have any mathematical meaning. Categorical data is displayed graphically by bar charts and pie charts. When it comes to categorical data examples, it can be given a wide range of examples. In our previous post nominal vs ordinal data, we provided a lot of examples of nominal variables (nominal data is the main type of categorical data). Examples of categorical data: Gender (Male, Female)
Brand of soaps (Dove, Olay…)
Hair color (Blonde, Brunette, Brown, Red, etc.) Survey on a topic “Do you have children?” ( Yes or No)
Motives for employees to work better: ( Peer Motivation, To Be Recognized, Opportunities for Professional Growth, Work Culture, the Feeling To Be Involved and etc.) Motives for traveling (Leisure, Business Travel, To Visit Friends and etc.) | 2,980 | 3,810 |
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| Gender (Male, Female)
Brand of soaps (Dove, Olay…)
Hair color (Blonde, Brunette, Brown, Red, etc.) Survey on a topic “Do you have children?” ( Yes or No)
Motives for employees to work better: ( Peer Motivation, To Be Recognized, Opportunities for Professional Growth, Work Culture, the Feeling To Be Involved and etc.) Motives for traveling (Leisure, Business Travel, To Visit Friends and etc.) Checking account location (California, Texas, Colorado…)
Educational level: ( Associate’s degree, Bachelor’s degree, Master’s degree, Doctoral degree and etc.) Age group (under 12 years old, 12-17 years old, 18-24 years old, 25-34 years old, 35-44 years old and etc.) Ethnicity (Hispanic, African American, Native American, Asian, Other)
Eye color (Green, Blue, Brown, Black)
Household Composition (Single, Married, Widowed, Divorced)
Employment status (Employed for wages, Self-employed, A homemaker, A student, Retired and etc.) Film Genres (Action, Adventure, Comedy, Crime, Mystery, Drama, Historical and etc)
Home country (Canada, USA, Australia, India, Germany). | 3,417 | 4,478 |
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| Checking account location (California, Texas, Colorado…)
Educational level: ( Associate’s degree, Bachelor’s degree, Master’s degree, Doctoral degree and etc.) Age group (under 12 years old, 12-17 years old, 18-24 years old, 25-34 years old, 35-44 years old and etc.) Ethnicity (Hispanic, African American, Native American, Asian, Other)
Eye color (Green, Blue, Brown, Black)
Household Composition (Single, Married, Widowed, Divorced)
Employment status (Employed for wages, Self-employed, A homemaker, A student, Retired and etc.) Film Genres (Action, Adventure, Comedy, Crime, Mystery, Drama, Historical and etc)
Home country (Canada, USA, Australia, India, Germany). Car color (Red, Green, Grey, Black, White and etc.) Religion (Muslin, Buddhist, Christian). Reasons for buying a present (Birthday, Anniversary, and etc.) Seasons (Winter, Spring, Summer, Autumn)
Holidays (Thanksgiving, Halloween)
Types of pet (Dog, Cat, Hamster)
Blood groups (Group A, Group B, Group AB, Group O). When categorical data has only 2 possible values, it is called binary. | 3,810 | 4,865 |
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| Car color (Red, Green, Grey, Black, White and etc.) Religion (Muslin, Buddhist, Christian). Reasons for buying a present (Birthday, Anniversary, and etc.) Seasons (Winter, Spring, Summer, Autumn)
Holidays (Thanksgiving, Halloween)
Types of pet (Dog, Cat, Hamster)
Blood groups (Group A, Group B, Group AB, Group O). When categorical data has only 2 possible values, it is called binary. If we use the categorical data examples above, the results of gender survey (male and female) and the survey on a topic “Do you have children?” ( Yes or No) are examples of binary data. Categorical and Quantitative (Numerical) Data: Difference
Sometimes, it is difficult to distinguish between categorical and quantitative data. Quantitative data is measured and expressed numerically. | 4,478 | 5,250 |
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| If we use the categorical data examples above, the results of gender survey (male and female) and the survey on a topic “Do you have children?” ( Yes or No) are examples of binary data. Categorical and Quantitative (Numerical) Data: Difference
Sometimes, it is difficult to distinguish between categorical and quantitative data. Quantitative data is measured and expressed numerically. It has numerical meaning and is used in calculations and arithmetic. That is why the other name of quantitative data is numerical. Examples of quantitative data are: weight, temperature, height, GPA, annual income, number of hours spent working and etc. More examples you can see on the ThoughtGo article “Quantitative Data”. | 4,866 | 5,576 |
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| It has numerical meaning and is used in calculations and arithmetic. That is why the other name of quantitative data is numerical. Examples of quantitative data are: weight, temperature, height, GPA, annual income, number of hours spent working and etc. More examples you can see on the ThoughtGo article “Quantitative Data”. In comparison, the categorical data does not have any numerical or quantitative meaning. It just describes qualitative characteristics of something. Types of quantitative data are: ordinal, interval, and ratio. Categorical data is always one type – the nominal type. | 5,251 | 5,843 |
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| In comparison, the categorical data does not have any numerical or quantitative meaning. It just describes qualitative characteristics of something. Types of quantitative data are: ordinal, interval, and ratio. Categorical data is always one type – the nominal type. The distinction between categorical and quantitative variables is crucial for deciding which types of data analysis methods to use. Quantitative data are analyzed using descriptive statistics, time series, linear regression models, and much more. For categorical data, typically only graphical and descriptive methods are used. Download the following infographic in PDF
Conclusion
As you see a lot of categorical data examples can be given to understand the meaning and purpose of the qualitative data. When working with data management or statistical sciences, it’s crucial to clearly understand some of the main terms, including quantitative and categorical data and what is their role. | 5,576 | 6,532 |
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| The distinction between categorical and quantitative variables is crucial for deciding which types of data analysis methods to use. Quantitative data are analyzed using descriptive statistics, time series, linear regression models, and much more. For categorical data, typically only graphical and descriptive methods are used. Download the following infographic in PDF
Conclusion
As you see a lot of categorical data examples can be given to understand the meaning and purpose of the qualitative data. When working with data management or statistical sciences, it’s crucial to clearly understand some of the main terms, including quantitative and categorical data and what is their role. It is important to get the meaning on the terminology right from the beginning, so when it comes time to deal with the real data problems, you will be able to work with them in the right way. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. Leave a Reply
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This site uses Akismet to reduce spam. Learn how your comment data is processed. | 5,843 | 7,153 |
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| 10 Best Content Analysis Software: Text Data Mining Tools
Best Text Analysis Software Tools
In our big data era, best content analysis software programs (also called document analysis tools or text mining software) are more than crucial. They help you to examine almost any type of unstructured text data such as business documents, emails, social media, chats, comments, news, blogs, competitor websites, marketing surveys questions, customer feedbacks, product reviews, call center transcripts and even scientific documents. They come in many forms: premium or free online text analysis tools, on-premise document analysis software for MAC and Windows and etc. On this page, we collected 10 of the top software for content analysis to allow you gain valuable insights from a large amount of unstructured data. 1. Word Stat
WordStat is a flexible and very easy-to-use content analysis and text mining software tool for handling large amounts of data. It helps you to quickly extract themes, patterns, and trends and analyze unstructured and structured data from many types of documents. You can use Word Stat for a wide variety of content examing activities such as: | 0 | 1,167 |
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| On this page, we collected 10 of the top software for content analysis to allow you gain valuable insights from a large amount of unstructured data. 1. Word Stat
WordStat is a flexible and very easy-to-use content analysis and text mining software tool for handling large amounts of data. It helps you to quickly extract themes, patterns, and trends and analyze unstructured and structured data from many types of documents. You can use Word Stat for a wide variety of content examing activities such as: analysis of interview or focus group transcripts, competitive websites analysis, business intelligence, information extraction from customer complaints and etc. In addition, Word Stat can analyze news coverage or scientific literature or can help you in fraud detection, patent analysis, and authorship attribution. Key Benefits and Features: Text processing capabilities. Integrated explanatory text mining and visualization tools such as clustering, proximity plots, and more. | 662 | 1,646 |
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| analysis of interview or focus group transcripts, competitive websites analysis, business intelligence, information extraction from customer complaints and etc. In addition, Word Stat can analyze news coverage or scientific literature or can help you in fraud detection, patent analysis, and authorship attribution. Key Benefits and Features: Text processing capabilities. Integrated explanatory text mining and visualization tools such as clustering, proximity plots, and more. Relates unstructured to structured data such as dates, numbers or categorical data for identifying temporal trends. Univariate keyword frequency analysis. Keyword retrieval function and keyword co-occurrence analysis. Analysis of case or document similarity. Automated text classification and many others. | 1,168 | 1,952 |
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| Relates unstructured to structured data such as dates, numbers or categorical data for identifying temporal trends. Univariate keyword frequency analysis. Keyword retrieval function and keyword co-occurrence analysis. Analysis of case or document similarity. Automated text classification and many others. Operating Systems: Microsoft Windows XP, 2000, Vista, Windows 7, 8 and 10, Mac OS, Linux. Website: https://provalisresearch.com/
2. Lexalytics
When it comes to the best content analysis software and tools, Lexalytics definitely has a top place here. | 1,646 | 2,202 |
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| Operating Systems: Microsoft Windows XP, 2000, Vista, Windows 7, 8 and 10, Mac OS, Linux. Website: https://provalisresearch.com/
2. Lexalytics
When it comes to the best content analysis software and tools, Lexalytics definitely has a top place here. Lexalytics makes cloud and on-premise text and sentiment analysis solutions that help you to transform customers’ thoughts and conversations into valuable and actionable insights. Lexalytics’ products SaaS Semantria and on-premise Salience are integrated into platforms for social media monitoring, survey analysis, reputation management, market research, and many other content analysis activities. Key Benefits and Features: Named entity extraction for identifying named text figures such as people, places, and brands, specific abbreviations, street addresses, phone numbers and whatever else you want. Themes to deals with multiple meaning words. | 1,952 | 2,853 |
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| Lexalytics makes cloud and on-premise text and sentiment analysis solutions that help you to transform customers’ thoughts and conversations into valuable and actionable insights. Lexalytics’ products SaaS Semantria and on-premise Salience are integrated into platforms for social media monitoring, survey analysis, reputation management, market research, and many other content analysis activities. Key Benefits and Features: Named entity extraction for identifying named text figures such as people, places, and brands, specific abbreviations, street addresses, phone numbers and whatever else you want. Themes to deals with multiple meaning words. Categories. Intentions such as Buy, Sell, Recommend, and Quit. Sentiment analysis to show you how consumers feel about their subject. Natural language processing engine. Salience is available for Microsoft Windows and Linux servers. | 2,202 | 3,086 |
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| Categories. Intentions such as Buy, Sell, Recommend, and Quit. Sentiment analysis to show you how consumers feel about their subject. Natural language processing engine. Salience is available for Microsoft Windows and Linux servers. Semantria API is for analyzing documents in the cloud. Website: https://www.lexalytics.com
3. DiscoverText
They are some kind of innovators. DiscoverText combines adaptive software algorithms with human-based coding for conducting large-scale analyses. | 2,853 | 3,339 |
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| Semantria API is for analyzing documents in the cloud. Website: https://www.lexalytics.com
3. DiscoverText
They are some kind of innovators. DiscoverText combines adaptive software algorithms with human-based coding for conducting large-scale analyses. The software can merge unstructured data from different sources. Examples of unstructured data are different documents and text files, open-ended answers on surveys, emails, and other offline and online text sources. With one platform, you can maintain your data quality metrics, you can capture, filter, de-duplicate, search, cluster, human code, and machine-classify large numbers of small text units. Key Benefits and Features: Advanced, multi-faceted power tool for text analysis. | 3,087 | 3,824 |
msmarco_v2.1_doc_01_1668182563#8_2446144306 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| The software can merge unstructured data from different sources. Examples of unstructured data are different documents and text files, open-ended answers on surveys, emails, and other offline and online text sources. With one platform, you can maintain your data quality metrics, you can capture, filter, de-duplicate, search, cluster, human code, and machine-classify large numbers of small text units. Key Benefits and Features: Advanced, multi-faceted power tool for text analysis. Schedule repeat fetches of live feeds via API. Classification via automation and manual training. Attach memos to documents and datasets. Redact sensitive information. Connect and work with the team via your browser. | 3,339 | 4,041 |
msmarco_v2.1_doc_01_1668182563#9_2446145379 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Schedule repeat fetches of live feeds via API. Classification via automation and manual training. Attach memos to documents and datasets. Redact sensitive information. Connect and work with the team via your browser. Generate high-level summary. Build topic models to automate. Enjoy a cloud-hosted application. Share projects, re-use models, and update results. Website: | 3,824 | 4,196 |
msmarco_v2.1_doc_01_1668182563#10_2446146122 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Generate high-level summary. Build topic models to automate. Enjoy a cloud-hosted application. Share projects, re-use models, and update results. Website: https://discovertext.com
4. Rapid Miner Text Extension
If you are searching for the best free content analysis software , Rapid Miner Text Extension worth considering. It is an extension of the popular free and open source data science software platform – Rapid Miner. Rapid Miner Text Extension has it all for statistical text analysis and Natural Language Processing (NLP). It allows you to load texts from a variety of data sources and documents, transform them and effortlessly analyze your content. | 4,041 | 4,700 |
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| https://discovertext.com
4. Rapid Miner Text Extension
If you are searching for the best free content analysis software , Rapid Miner Text Extension worth considering. It is an extension of the popular free and open source data science software platform – Rapid Miner. Rapid Miner Text Extension has it all for statistical text analysis and Natural Language Processing (NLP). It allows you to load texts from a variety of data sources and documents, transform them and effortlessly analyze your content. Key Benefits and Features: Supports many text formats including plain text, HTML, or PDF. Provides standard filters for tokenization, stemming, stop word filtering or n-gram generation. Document class that stores the whole documents in combination with additional meta information. Statistical text analysis. | 4,197 | 5,009 |
msmarco_v2.1_doc_01_1668182563#12_2446148352 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Key Benefits and Features: Supports many text formats including plain text, HTML, or PDF. Provides standard filters for tokenization, stemming, stop word filtering or n-gram generation. Document class that stores the whole documents in combination with additional meta information. Statistical text analysis. You have to be a member of the RapidMiner community to use their Text Extension. You can join the community and use all the RapidMiner extensions for free. Website: https://marketplace.rapidminer.com/
5. SAS Text Miner
No doubt that SAS is one of the biggest names in the business intelligence and data mining industry. | 4,700 | 5,329 |
msmarco_v2.1_doc_01_1668182563#13_2446149355 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| You have to be a member of the RapidMiner community to use their Text Extension. You can join the community and use all the RapidMiner extensions for free. Website: https://marketplace.rapidminer.com/
5. SAS Text Miner
No doubt that SAS is one of the biggest names in the business intelligence and data mining industry. Their Text Miner product can bring you fast and deep insight from a wide variety of unstructured documents and other data types. The software allows you easily analyze text data from the web, books, comment fields, and many other text sources. The tool automatically reads text data and deliver advanced analysis algorithms to help you catch trends and take new opportunities. Key Benefits and Features: High-performance text mining to help you quickly evaluate a large number of document collections. | 5,009 | 5,831 |
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| Their Text Miner product can bring you fast and deep insight from a wide variety of unstructured documents and other data types. The software allows you easily analyze text data from the web, books, comment fields, and many other text sources. The tool automatically reads text data and deliver advanced analysis algorithms to help you catch trends and take new opportunities. Key Benefits and Features: High-performance text mining to help you quickly evaluate a large number of document collections. Processing interface conforms to Windows accessibility standards. Automatic Boolean rule generation to easily classify content. Term profiling and trending. Document theme discovery. Native support for multiple languages. | 5,330 | 6,053 |
msmarco_v2.1_doc_01_1668182563#15_2446151647 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Processing interface conforms to Windows accessibility standards. Automatic Boolean rule generation to easily classify content. Term profiling and trending. Document theme discovery. Native support for multiple languages. Determine what’s hot and what’s not. Website: https://www.sas.com
6. Text2data
Text2data is a great product for those who are looking for affordable text mining and content analysis software. This is an NLP/ Deep Learning (Natural Language Processing) platform with proprietary algorithms that provide cloud-based text analytics services for understanding your customers better. | 5,831 | 6,432 |
msmarco_v2.1_doc_01_1668182563#16_2446152632 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Determine what’s hot and what’s not. Website: https://www.sas.com
6. Text2data
Text2data is a great product for those who are looking for affordable text mining and content analysis software. This is an NLP/ Deep Learning (Natural Language Processing) platform with proprietary algorithms that provide cloud-based text analytics services for understanding your customers better. No matter if you want to analyze social media, emails, free-text survey questions or other sources of information about your customers’ experiences, the system got you covered. Key Benefits and Features: Sentiment analysis to identify and extract subjective information in a text document. Text/ Document summarization. Document classification based on pre-trained data models. | 6,053 | 6,810 |
msmarco_v2.1_doc_01_1668182563#17_2446153778 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| No matter if you want to analyze social media, emails, free-text survey questions or other sources of information about your customers’ experiences, the system got you covered. Key Benefits and Features: Sentiment analysis to identify and extract subjective information in a text document. Text/ Document summarization. Document classification based on pre-trained data models. Entity extraction as the names of persons, organizations, locations etc. Themes discovery that can significantly improve the inferring context of the document. Keyword analysis of the documents and assigning the sentiment score to them. Citation detection. Slang detection. | 6,432 | 7,084 |
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| Entity extraction as the names of persons, organizations, locations etc. Themes discovery that can significantly improve the inferring context of the document. Keyword analysis of the documents and assigning the sentiment score to them. Citation detection. Slang detection. Website: http://text2data.org/
7. Etuma
Etuma Text Analysis is one of the top content analysis software tools able to turn your open-ended customer feedbacks into actionable information. Etuma serves a wide variety of business domains such as customer experience management, competitor analysis, market analysis and intelligence, contact centers, sentiment analysis, voice of the customer (research surveys), social media monitoring, employee engagement, and chat analysis. Etuma discovers in real-time what your customers like and dislike about your products. | 6,810 | 7,645 |
msmarco_v2.1_doc_01_1668182563#19_2446156016 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Website: http://text2data.org/
7. Etuma
Etuma Text Analysis is one of the top content analysis software tools able to turn your open-ended customer feedbacks into actionable information. Etuma serves a wide variety of business domains such as customer experience management, competitor analysis, market analysis and intelligence, contact centers, sentiment analysis, voice of the customer (research surveys), social media monitoring, employee engagement, and chat analysis. Etuma discovers in real-time what your customers like and dislike about your products. Etuma is a SaaS product that runs in the cloud. Key Benefits and Features: Multi-language – understand several languages – results in one language. Automatic software with no human work. It uses Natural Language Processing (NLP) and Artificial Intelligence. | 7,084 | 7,903 |
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| Etuma is a SaaS product that runs in the cloud. Key Benefits and Features: Multi-language – understand several languages – results in one language. Automatic software with no human work. It uses Natural Language Processing (NLP) and Artificial Intelligence. Consistent – relevant industry-specific categorization. Discovers in real-time what your customers like and dislike. Can analyze any type of feedback. Easy to integrate – the tool has connectors to a variety of survey, contact center, and customer experience management platforms such as Salesforce, Zendeck and etc. A large number of text analysis and text mining functions such as syntactic parsing, word count, tokenization roots, word stemming, end of sentence detection, part of speech (POS) identifications, spelling correction, synonyms, semantic topic, sentiment detection and etc. | 7,646 | 8,493 |
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| Consistent – relevant industry-specific categorization. Discovers in real-time what your customers like and dislike. Can analyze any type of feedback. Easy to integrate – the tool has connectors to a variety of survey, contact center, and customer experience management platforms such as Salesforce, Zendeck and etc. A large number of text analysis and text mining functions such as syntactic parsing, word count, tokenization roots, word stemming, end of sentence detection, part of speech (POS) identifications, spelling correction, synonyms, semantic topic, sentiment detection and etc. Website: www.etuma.com
8. Luminoso
Luminoso is a great text mining and analysis tool that deals with a large number of unstructured data to enable you to quickly surface key topics, identify the conversations that matter, tab into customer services, and track trends over time. This easy to use tool allows you to quickly explore and analyze data like open-ended survey responses, product reviews, and call center transcripts. The software uses the latest methods in artificial intelligence and natural language understanding to help you in a variety of business challenges like understanding key drivers behind NPS scores and classifying customer support tickets. | 7,903 | 9,158 |
msmarco_v2.1_doc_01_1668182563#22_2446160098 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Website: www.etuma.com
8. Luminoso
Luminoso is a great text mining and analysis tool that deals with a large number of unstructured data to enable you to quickly surface key topics, identify the conversations that matter, tab into customer services, and track trends over time. This easy to use tool allows you to quickly explore and analyze data like open-ended survey responses, product reviews, and call center transcripts. The software uses the latest methods in artificial intelligence and natural language understanding to help you in a variety of business challenges like understanding key drivers behind NPS scores and classifying customer support tickets. Key Benefits and Features: Quickly uncover high-value insights in your text data. Can natively analyze data in 13 languages, including English, Arabic, Chinese, Spanish, and Russian. Within minutes, Luminoso Text Analytics identifies key topics, meaningful connections, and trends. Latest methods in artificial intelligence and natural language understanding. | 8,493 | 9,518 |
msmarco_v2.1_doc_01_1668182563#23_2446161497 | http://intellspot.com/content-analysis-software/ | 10 Best Content Analysis Software: Text Data Mining Tools | Best Text Analysis Software Tools
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| Key Benefits and Features: Quickly uncover high-value insights in your text data. Can natively analyze data in 13 languages, including English, Arabic, Chinese, Spanish, and Russian. Within minutes, Luminoso Text Analytics identifies key topics, meaningful connections, and trends. Latest methods in artificial intelligence and natural language understanding. Flexible outputs and intuitive dashboards that make reporting and sharing easy
Analyzing contact center data. Uncover connections between employees’ engagement levels and customers’ satisfaction. Understand caregiving needs by analyzing text data from online communities. Website: https://luminoso.com
9. | 9,158 | 9,823 |
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| Flexible outputs and intuitive dashboards that make reporting and sharing easy
Analyzing contact center data. Uncover connections between employees’ engagement levels and customers’ satisfaction. Understand caregiving needs by analyzing text data from online communities. Website: https://luminoso.com
9. Pingar DiscoveryOne
Pingar DiscoveryOne is a content analysis software designed to let enterprises discover opportunities and risks hidden in the text of web and corporate data | 9,518 | 10,000 |
msmarco_v2.1_doc_01_1668196877#0_2446163414 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Cool Ways to Show Data: 15 Creative Methods to Present Data
15 Cool Ways to Show Data
You might be surprised at the great number of interesting, creative, and cool ways to show data and present information. In today business world, data visualization and presentation have a critical role in making people understand the importance of data results and analysis. The different methods of showing data in a pictorial form, graphical, and visual context enable decision-makers to grasp difficult concepts or define trends. No matter if you want to visualize a data flow, data comparison or you need to show data over time as a trend, there are many variants of visual communication. Here we collected 15 examples of creative and cool ways to show data in statistics, business, marketing, finance and etc. 1. Venn Diagram
If you need to make a comparison between 2 relatively simple data sets, Venn diagram can be your creative and cool solution. Venn diagram is an illustration that uses circles to shows logical relationships between two or more sets (grouping items). Typically, Venn diagrams show how given items are similar and different. | 0 | 1,139 |
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| Here we collected 15 examples of creative and cool ways to show data in statistics, business, marketing, finance and etc. 1. Venn Diagram
If you need to make a comparison between 2 relatively simple data sets, Venn diagram can be your creative and cool solution. Venn diagram is an illustration that uses circles to shows logical relationships between two or more sets (grouping items). Typically, Venn diagrams show how given items are similar and different. Venn diagram with 2 or 3 circles is the most common type. But there are also many diagrams with a larger number of circles (5,6,7,8,10…). 2. Bubble Chart
Bubble Chart is one of the most attractive types of graphs and charts available in statistics and business. Bubble charts are super useful charts for making a comparison of the relationships between data in 3 numeric data dimensions: | 679 | 1,527 |
msmarco_v2.1_doc_01_1668196877#2_2446166194 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Venn diagram with 2 or 3 circles is the most common type. But there are also many diagrams with a larger number of circles (5,6,7,8,10…). 2. Bubble Chart
Bubble Chart is one of the most attractive types of graphs and charts available in statistics and business. Bubble charts are super useful charts for making a comparison of the relationships between data in 3 numeric data dimensions: the Y-axis data, the X-axis data, and data depicting the bubble size. If you want to display three or four dimensions of data or you want to compare and display the relationships between categorized circles, bubble charts can be your answer. 3. Decision Trees
As graphical representations of complex or simple problems, decision trees have an important place in business. A decision tree is a diagram representation of possible solutions to a decision. | 1,140 | 1,980 |
msmarco_v2.1_doc_01_1668196877#3_2446167435 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| the Y-axis data, the X-axis data, and data depicting the bubble size. If you want to display three or four dimensions of data or you want to compare and display the relationships between categorized circles, bubble charts can be your answer. 3. Decision Trees
As graphical representations of complex or simple problems, decision trees have an important place in business. A decision tree is a diagram representation of possible solutions to a decision. It shows different outcomes from a set of decisions. Decision trees are helpful for a variety of reasons. Not only they are easy-to-understand diagrams that support you ‘see’ your thoughts, but also because they provide a framework for estimating all possible alternatives. 4. Radar Chart
A radar chart is one of the most modern types of charts and cool ways to show data – ideal for multiple comparisons. | 1,528 | 2,386 |
msmarco_v2.1_doc_01_1668196877#4_2446168704 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| It shows different outcomes from a set of decisions. Decision trees are helpful for a variety of reasons. Not only they are easy-to-understand diagrams that support you ‘see’ your thoughts, but also because they provide a framework for estimating all possible alternatives. 4. Radar Chart
A radar chart is one of the most modern types of charts and cool ways to show data – ideal for multiple comparisons. Radar charts use a circular display with several different quantitative axes looking like spokes on a wheel. Each axis shows a quantity for a different categorical value. Radar Chart has many applications nowadays in statistics, maths, business, sports analysis, data intelligence, and etc. 5. Cycle Diagram
Cycle diagram is a rarely used method for data visualization and representation. | 1,981 | 2,775 |
msmarco_v2.1_doc_01_1668196877#5_2446169909 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Radar charts use a circular display with several different quantitative axes looking like spokes on a wheel. Each axis shows a quantity for a different categorical value. Radar Chart has many applications nowadays in statistics, maths, business, sports analysis, data intelligence, and etc. 5. Cycle Diagram
Cycle diagram is a rarely used method for data visualization and representation. However, it has some interesting benefits and an attractive look. Cycle Diagram shows how one event flows to another. It presents the steps of a cyclical process or a data flow. Cycle diagrams can be utilized for many different types of processes. For example, you can use Circle diagram to visualize a flow of money in a company or the path of assets that run through a production process. | 2,387 | 3,166 |
msmarco_v2.1_doc_01_1668196877#6_2446171083 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| However, it has some interesting benefits and an attractive look. Cycle Diagram shows how one event flows to another. It presents the steps of a cyclical process or a data flow. Cycle diagrams can be utilized for many different types of processes. For example, you can use Circle diagram to visualize a flow of money in a company or the path of assets that run through a production process. 6. Concept Maps
Concept maps (also known as mind maps) are among the most interesting and cool ways to show data. They are widely used for organizing thoughts, ideas, brainstorming and solving complex business problems. With the help of a mind map, you can represent and link ideas so you can choose the most critical points and solutions. There are many free mind mapping tools you can use for different purposes. | 2,776 | 3,581 |
msmarco_v2.1_doc_01_1668196877#7_2446172283 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| 6. Concept Maps
Concept maps (also known as mind maps) are among the most interesting and cool ways to show data. They are widely used for organizing thoughts, ideas, brainstorming and solving complex business problems. With the help of a mind map, you can represent and link ideas so you can choose the most critical points and solutions. There are many free mind mapping tools you can use for different purposes. 7. Flowchart
For those who want to communicate a process at a glance, flowcharts are wonderful ways to represent data. A flowchart allows you to show the sequence of steps involved in a process using symbols, shapes, arrows, text or other geometric elements. A flowchart is a powerful visualization tool and one of the most popular, creative, and cool ways to show data in the business. With proper design, it allows understanding the steps in a process very effectively and efficiently. | 3,166 | 4,069 |
msmarco_v2.1_doc_01_1668196877#8_2446173581 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| 7. Flowchart
For those who want to communicate a process at a glance, flowcharts are wonderful ways to represent data. A flowchart allows you to show the sequence of steps involved in a process using symbols, shapes, arrows, text or other geometric elements. A flowchart is a powerful visualization tool and one of the most popular, creative, and cool ways to show data in the business. With proper design, it allows understanding the steps in a process very effectively and efficiently. 8. Fishbone Diagram
When it comes to creative ways to visualize data, fishbone diagram is definitely one of the best data representing tools. Fishbone diagram is known as one of the key graphical methods to solve business problems because it takes into account all the possible causes. A fishbone diagram (also known as a cause and effect diagram or Ishikawa diagram) is a visualization tool for categorizing the possible causes of a particular problem or situation. The main goal is to find the root cause. | 3,581 | 4,577 |
msmarco_v2.1_doc_01_1668196877#9_2446174972 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| 8. Fishbone Diagram
When it comes to creative ways to visualize data, fishbone diagram is definitely one of the best data representing tools. Fishbone diagram is known as one of the key graphical methods to solve business problems because it takes into account all the possible causes. A fishbone diagram (also known as a cause and effect diagram or Ishikawa diagram) is a visualization tool for categorizing the possible causes of a particular problem or situation. The main goal is to find the root cause. Therefore, it is one of the key root cause analysis tools. Although it looks difficult for drawing, there are many free fishbone diagram software tools that make creating Ishikawa diagram a piece of cake. 9. Scatter Plot
Scatter Plot can be very interesting and attractive method for representing a relationship between 2 variables. Scatter Plot is an X-Y diagram that shows a correlation between two variables. | 4,069 | 4,989 |
msmarco_v2.1_doc_01_1668196877#10_2446176287 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Therefore, it is one of the key root cause analysis tools. Although it looks difficult for drawing, there are many free fishbone diagram software tools that make creating Ishikawa diagram a piece of cake. 9. Scatter Plot
Scatter Plot can be very interesting and attractive method for representing a relationship between 2 variables. Scatter Plot is an X-Y diagram that shows a correlation between two variables. It is utilized to plot data points on a vertical and a horizontal axis. The goal is to represent how much one variable affects another. 10. Box and Whisker Plot
Not only their name but also the way they look make you think box and whisker plots are cool ways to show data in statistic or in business. A box and whisker plot (or just a box plot) is a graph that represents visually data from a five-number summary. | 4,578 | 5,403 |
msmarco_v2.1_doc_01_1668196877#11_2446177509 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| It is utilized to plot data points on a vertical and a horizontal axis. The goal is to represent how much one variable affects another. 10. Box and Whisker Plot
Not only their name but also the way they look make you think box and whisker plots are cool ways to show data in statistic or in business. A box and whisker plot (or just a box plot) is a graph that represents visually data from a five-number summary. These numbers are median, upper and lower quartile, minimum, and maximum data value (extremes). Don’t panic, these numbers are easy to understand. For more details take a look at our post box and whisker plot examples. 11. Pie Charts
Pie Charts are a classic way to present data but still, it is one of the coolest and most attractive methods. | 4,990 | 5,747 |
msmarco_v2.1_doc_01_1668196877#12_2446178668 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| These numbers are median, upper and lower quartile, minimum, and maximum data value (extremes). Don’t panic, these numbers are easy to understand. For more details take a look at our post box and whisker plot examples. 11. Pie Charts
Pie Charts are a classic way to present data but still, it is one of the coolest and most attractive methods. Pie charts display data and statistics in an easy-to-understand ‘pie-slice’ format and illustrate numerical proportion. The pie chart brakes down a group into smaller pieces. It shows part-whole relationships. To make a pie chart, you need a list of categorical data and numerical variables. The total sum of the proportions (pieces) is 100%. | 5,404 | 6,090 |
msmarco_v2.1_doc_01_1668196877#13_2446179765 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Pie charts display data and statistics in an easy-to-understand ‘pie-slice’ format and illustrate numerical proportion. The pie chart brakes down a group into smaller pieces. It shows part-whole relationships. To make a pie chart, you need a list of categorical data and numerical variables. The total sum of the proportions (pieces) is 100%. 12. Pictographs
The pictograph is one of the most eye-catching ways of showing data in a pictorial form. It displays numerical information with the use of icons or picture symbols to represent data sets. They are very easy to read statistical way of data visualization. A pictogram shows the frequency of data as images or symbols. | 5,748 | 6,422 |
msmarco_v2.1_doc_01_1668196877#14_2446180845 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| 12. Pictographs
The pictograph is one of the most eye-catching ways of showing data in a pictorial form. It displays numerical information with the use of icons or picture symbols to represent data sets. They are very easy to read statistical way of data visualization. A pictogram shows the frequency of data as images or symbols. Each image/symbol may represent one or more units of a given dataset. 13. Gantt Chart
As a powerful tool at the hands of project managers, Gantt chart is a graphical illustration that represents a project schedule or a timeline. Actually, this is very useful and interesting way of showing tasks displayed against time. Gantt chart is irreplaceable when it comes to using tools for planning, coordinating, and tracking specific activities in a project. | 6,090 | 6,875 |
msmarco_v2.1_doc_01_1668196877#15_2446182026 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Each image/symbol may represent one or more units of a given dataset. 13. Gantt Chart
As a powerful tool at the hands of project managers, Gantt chart is a graphical illustration that represents a project schedule or a timeline. Actually, this is very useful and interesting way of showing tasks displayed against time. Gantt chart is irreplaceable when it comes to using tools for planning, coordinating, and tracking specific activities in a project. 14. Funnel Chart
Funnel charts are great ways to illustrate stages in a specific process, most common – a sales process. Actually, they could be utilized to show anything that’s decreasing in size. Funnel charts are very similar to pie charts because the total sum of the bars is 100%. Each funnel stage illustrates a percentage of the whole. | 6,423 | 7,218 |
msmarco_v2.1_doc_01_1668196877#16_2446183228 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| 14. Funnel Chart
Funnel charts are great ways to illustrate stages in a specific process, most common – a sales process. Actually, they could be utilized to show anything that’s decreasing in size. Funnel charts are very similar to pie charts because the total sum of the bars is 100%. Each funnel stage illustrates a percentage of the whole. Typically, the first stage is the largest, and each next stage is smaller than its predecessor. 15. Pyramid Graph
Definitely, pyramid graphs are very cool ways to show data. Moreover, they are absolutely easy to understand charts. A pyramid graph is a chart in a pyramid shape or triangle shape. | 6,875 | 7,514 |
msmarco_v2.1_doc_01_1668196877#17_2446184273 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| Typically, the first stage is the largest, and each next stage is smaller than its predecessor. 15. Pyramid Graph
Definitely, pyramid graphs are very cool ways to show data. Moreover, they are absolutely easy to understand charts. A pyramid graph is a chart in a pyramid shape or triangle shape. These types of charts are best for data that is organized in some kind of hierarchy. The levels show a progressive order. How to create cool charts and graphs? The short answer – with the right software tools. In our high-tech era, there is a wide variety of premium or free graphing software tools that allow you to create amazing graphs and charts in minutes. | 7,219 | 7,876 |
msmarco_v2.1_doc_01_1668196877#18_2446185331 | http://intellspot.com/cool-ways-to-show-data/ | Cool Ways to Show Data: 15 Creative Methods to Present Data | 15 Cool Ways to Show Data
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| These types of charts are best for data that is organized in some kind of hierarchy. The levels show a progressive order. How to create cool charts and graphs? The short answer – with the right software tools. In our high-tech era, there is a wide variety of premium or free graphing software tools that allow you to create amazing graphs and charts in minutes. They are interesting, visually-appealing, and easy to understand. Here is a list of the most popular of them: SmartDraw
Lucidchart
FusionCharts
Infogr.am
AmCharts
Highcharts
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Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc. Leave a Reply
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