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msmarco_v2.1_doc_01_1668456031#12_2446795445 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
Qualitative Data Analysis Methods And Techniques
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| What can we discover from the narrative analysis? An interesting knowledge and understandings about people, their culture and how they are changing. It helps us making sense of the past and create meanings of it. Helps in organizing information about how humans interpret events. Show us the values and beliefs that guide those interpretations. A long number of data collection methods can be performed. Data can be in the form of journal records, interview transcripts, observations, autobiographical writing, documents, storytelling, personal accounts, letter writing, and etc. 4. Discourse Analysis
Discourse analysis is about analyzing the natural occurring talk – spoken communication and all other types of text. It studies the meanings that the use of language and spoken interactions produce and the contexts of these meanings. | 5,049 | 5,885 |
msmarco_v2.1_doc_01_1668456031#13_2446796774 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
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| A long number of data collection methods can be performed. Data can be in the form of journal records, interview transcripts, observations, autobiographical writing, documents, storytelling, personal accounts, letter writing, and etc. 4. Discourse Analysis
Discourse analysis is about analyzing the natural occurring talk – spoken communication and all other types of text. It studies the meanings that the use of language and spoken interactions produce and the contexts of these meanings. This method not only analyses communications but also takes into consideration the social context in which the communications happen. This technique can also include analysis of written texts, such as emails or the body language. Discourse analysis is a field of linguistics that focuses on the role of language in the building of social reality. Typically, discourse analysis brings together the analysis of language use and the analysis of situations. 5. | 5,394 | 6,342 |
msmarco_v2.1_doc_01_1668456031#14_2446798215 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
Qualitative Data Analysis Methods And Techniques
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| This method not only analyses communications but also takes into consideration the social context in which the communications happen. This technique can also include analysis of written texts, such as emails or the body language. Discourse analysis is a field of linguistics that focuses on the role of language in the building of social reality. Typically, discourse analysis brings together the analysis of language use and the analysis of situations. 5. Framework Analysis
Framework is one of the qualitative data analysis methods that are gaining popularity across multiple areas, including health, social policy, and psychology. This approach is used to organize and manage data with the help of the process of summarization. It results in a powerful and flexible matrix that allows you to analyze data both by theme and case. The matrix consists of rows (cases), columns (codes) and ‘cells’ of summarised data. Thus it provides a structure into which you can systematically cut the data, to analyze it by case and by code. | 5,885 | 6,914 |
msmarco_v2.1_doc_01_1668456031#15_2446799742 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
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| Framework Analysis
Framework is one of the qualitative data analysis methods that are gaining popularity across multiple areas, including health, social policy, and psychology. This approach is used to organize and manage data with the help of the process of summarization. It results in a powerful and flexible matrix that allows you to analyze data both by theme and case. The matrix consists of rows (cases), columns (codes) and ‘cells’ of summarised data. Thus it provides a structure into which you can systematically cut the data, to analyze it by case and by code. Using theme display, framework technique lets you analyze your data thematically and to perform exploratory analysis of the entire dataset. Framework analysis identifies similarities and differences in qualitative data, thereby aims to draw descriptive or explanatory conclusions grouped in themes. Framework analysis is one of the easiest qualitative data analysis techniques. It has very clear steps you can follow and makes highly structured outputs of summarised data. Download the following infographic in PDF for free
Conclusion
You have a good range of qualitative data analysis methods to choose from, in order to achieve the main purpose of qualitative analysis – to explain, understand, and interpret data. | 6,343 | 7,631 |
msmarco_v2.1_doc_01_1668456031#16_2446801536 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
Qualitative Data Analysis Methods And Techniques
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| Using theme display, framework technique lets you analyze your data thematically and to perform exploratory analysis of the entire dataset. Framework analysis identifies similarities and differences in qualitative data, thereby aims to draw descriptive or explanatory conclusions grouped in themes. Framework analysis is one of the easiest qualitative data analysis techniques. It has very clear steps you can follow and makes highly structured outputs of summarised data. Download the following infographic in PDF for free
Conclusion
You have a good range of qualitative data analysis methods to choose from, in order to achieve the main purpose of qualitative analysis – to explain, understand, and interpret data. There are many software solutions (such as Atlas.ti) designed to assist you with the analysis of qualitative data. Moreover, for the advanced users, there is a free qualitative data analysis software able to analyze a large amount of text. They have enhanced people’s ability to perform data analysis by handling multiple means and ways of collecting, sorting, presenting, and analyzing raw data. 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. | 6,914 | 8,349 |
msmarco_v2.1_doc_01_1668456031#17_2446803472 | http://intellspot.com/qualitative-data-analysis-methods/ | Qualitative Data Analysis Methods And Techniques | Qualitative Data Analysis Methods And Techniques
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| There are many software solutions (such as Atlas.ti) designed to assist you with the analysis of qualitative data. Moreover, for the advanced users, there is a free qualitative data analysis software able to analyze a large amount of text. They have enhanced people’s ability to perform data analysis by handling multiple means and ways of collecting, sorting, presenting, and analyzing raw data. 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. | 7,631 | 8,457 |
msmarco_v2.1_doc_01_1668465060#0_2446804794 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Qualitative vs Quantitative Data: Analysis, Definitions, Examples
Qualitative vs Quantitative Data: Definitions, Analysis, Examples
If you are involved in statistics, marketing or data science, it is essential to know what is the difference between qualitative and quantitative data and analysis. They are different approaches to understanding data and to perform analysis of information. We will define, explain, compare, and give examples of qualitative data versus quantitative data, variables, and analysis. On this page: Qualitative vs quantitative data: definition, examples, characteristics, contrast, similarities, and differences. What is quantitative data analysis? Steps and types. | 0 | 692 |
msmarco_v2.1_doc_01_1668465060#1_2446806045 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| On this page: Qualitative vs quantitative data: definition, examples, characteristics, contrast, similarities, and differences. What is quantitative data analysis? Steps and types. What is qualitative data analysis? Steps and types. Comparison chart in PDF (infographic). What is quantitative data? Quantitative data seems to be simpler to define and identify. | 511 | 872 |
msmarco_v2.1_doc_01_1668465060#2_2446806964 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| What is qualitative data analysis? Steps and types. Comparison chart in PDF (infographic). What is quantitative data? Quantitative data seems to be simpler to define and identify. Quantitative data is data that can be expressed as a number or can be quantified. In other words, quantitative data can be measured by numerical variables. Quantitative data are easily amenable to statistical manipulation and can be represented with a wide variety of statistical types of graphs and chards such as line, graph, bar graph, scatter plot, box and whisker plot and etc. Key characteristics of quantitative data: It can be quantified and verified. | 692 | 1,332 |
msmarco_v2.1_doc_01_1668465060#3_2446808163 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Quantitative data is data that can be expressed as a number or can be quantified. In other words, quantitative data can be measured by numerical variables. Quantitative data are easily amenable to statistical manipulation and can be represented with a wide variety of statistical types of graphs and chards such as line, graph, bar graph, scatter plot, box and whisker plot and etc. Key characteristics of quantitative data: It can be quantified and verified. Data can be counted. Data type: number and statistics. It answers questions such as “how many, “how much” and “how often”. Examples of quantitative data: | 872 | 1,486 |
msmarco_v2.1_doc_01_1668465060#4_2446809361 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Data can be counted. Data type: number and statistics. It answers questions such as “how many, “how much” and “how often”. Examples of quantitative data: Scores on tests and exams e.g. 85, 67, 90 and etc. The weight of a person or a subject. The number of hours of study. Your shoe size. The square feet of an apartment. | 1,332 | 1,653 |
msmarco_v2.1_doc_01_1668465060#5_2446810267 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Scores on tests and exams e.g. 85, 67, 90 and etc. The weight of a person or a subject. The number of hours of study. Your shoe size. The square feet of an apartment. The temperature in a room. The volume of a gas and etc. Types of quantitative data: There are 2 general types of quantitative data: Discrete data – a count that involves integers. | 1,486 | 1,833 |
msmarco_v2.1_doc_01_1668465060#6_2446811179 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| The temperature in a room. The volume of a gas and etc. Types of quantitative data: There are 2 general types of quantitative data: Discrete data – a count that involves integers. Only a limited number of values is possible. The discrete values cannot be subdivided into parts. For example, the number of children in a school is discrete data. You can count whole individuals. You can’t count 1.5 kids. | 1,653 | 2,056 |
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| Only a limited number of values is possible. The discrete values cannot be subdivided into parts. For example, the number of children in a school is discrete data. You can count whole individuals. You can’t count 1.5 kids. Continuous data – information that could be meaningfully divided into finer levels. It can be measured on a scale or continuum and can have almost any numeric value. For example, you can measure your height at very precise scales — meters, centimeters, millimeters and etc. More on the topic see in our post discrete vs continuous data. What is qualitative data? | 1,834 | 2,419 |
msmarco_v2.1_doc_01_1668465060#8_2446813313 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Continuous data – information that could be meaningfully divided into finer levels. It can be measured on a scale or continuum and can have almost any numeric value. For example, you can measure your height at very precise scales — meters, centimeters, millimeters and etc. More on the topic see in our post discrete vs continuous data. What is qualitative data? As you might guess qualitative data is information that can’t be expressed as a number and can’t be measured. Qualitative data consist of words, pictures, observations, and symbols, not numbers. It is about qualities. Qualitative data is also called categorical data. The reason is that the information can be sorted by category, not by number. | 2,056 | 2,764 |
msmarco_v2.1_doc_01_1668465060#9_2446814601 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| As you might guess qualitative data is information that can’t be expressed as a number and can’t be measured. Qualitative data consist of words, pictures, observations, and symbols, not numbers. It is about qualities. Qualitative data is also called categorical data. The reason is that the information can be sorted by category, not by number. Qualitative data is analyzed to look for common themes. Key characteristics of qualitative data: It cannot be quantified and verified. Data cannot be counted. Data type: | 2,419 | 2,934 |
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| Qualitative data is analyzed to look for common themes. Key characteristics of qualitative data: It cannot be quantified and verified. Data cannot be counted. Data type: words, objects, pictures, observations, and symbols. It answers questions such as “how this has happened” or and “why this has happened”. Examples of qualitative data: Your socioeconomic status
Colors e.g. the color of the sea
The Smell e.g. aromatic, buttery, camphoric and etc. Your favorite holiday destination such as Hawaii, New Zealand and etc. | 2,765 | 3,285 |
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| words, objects, pictures, observations, and symbols. It answers questions such as “how this has happened” or and “why this has happened”. Examples of qualitative data: Your socioeconomic status
Colors e.g. the color of the sea
The Smell e.g. aromatic, buttery, camphoric and etc. Your favorite holiday destination such as Hawaii, New Zealand and etc. Names as John, Patricia,…..
Sounds like bang and blare. Ethnicity such as American Indian, Asian, etc. Quantitative Data Analysis: Meaning, Steps, and Types
Quantitative data analysis ends with easy to understand and quantifiable results. You can analyze it in many different ways. | 2,935 | 3,567 |
msmarco_v2.1_doc_01_1668465060#12_2446818013 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Names as John, Patricia,…..
Sounds like bang and blare. Ethnicity such as American Indian, Asian, etc. Quantitative Data Analysis: Meaning, Steps, and Types
Quantitative data analysis ends with easy to understand and quantifiable results. You can analyze it in many different ways. But before starting the analysis you have to define the level of measurement involved in the quantitative data. Let’s see the steps in the process of analyzing quantitative variables. It will help us to see better the difference between qualitative and quantitative data analysis. Step 1: Identify the level of measurement
There are 4 scales/levels of measurement: | 3,285 | 3,932 |
msmarco_v2.1_doc_01_1668465060#13_2446819234 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| But before starting the analysis you have to define the level of measurement involved in the quantitative data. Let’s see the steps in the process of analyzing quantitative variables. It will help us to see better the difference between qualitative and quantitative data analysis. Step 1: Identify the level of measurement
There are 4 scales/levels of measurement: Nominal – data scales used simply for labeling variables, without quantitative value. The nominal data just name a thing without applying it to an order. Even though we can use the numbers, they do not denote quantity. Examples of nominal data: hair color (Blonde, Brown, Brunette, etc.). | 3,568 | 4,221 |
msmarco_v2.1_doc_01_1668465060#14_2446820460 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Nominal – data scales used simply for labeling variables, without quantitative value. The nominal data just name a thing without applying it to an order. Even though we can use the numbers, they do not denote quantity. Examples of nominal data: hair color (Blonde, Brown, Brunette, etc.). Ordinal . Ordinal data is placed into some kind of order by their position on the scale. They often indicate superiority. Example of ordinal data: the first, second and third person in a competition. | 3,932 | 4,421 |
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| Ordinal . Ordinal data is placed into some kind of order by their position on the scale. They often indicate superiority. Example of ordinal data: the first, second and third person in a competition. To understand better see our post nominal vs ordinal data. Interval – numerical scales that show information about an order. In interval scales, the intervals between each data value are the same. A popular example here is the temperature in centigrade, where, for instance, the interval between 930C and 950C is the same as the distance between 1060C and 1080C. However, there isn’t a starting point in the interval scales. See more interval data examples. | 4,221 | 4,879 |
msmarco_v2.1_doc_01_1668465060#16_2446822744 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| To understand better see our post nominal vs ordinal data. Interval – numerical scales that show information about an order. In interval scales, the intervals between each data value are the same. A popular example here is the temperature in centigrade, where, for instance, the interval between 930C and 950C is the same as the distance between 1060C and 1080C. However, there isn’t a starting point in the interval scales. See more interval data examples. Ratio – not only show order and have equal intervals, but they can also have a value of zero. Identifying the levels of measurement where a dataset falls under, will help you decide whether or not the data is useful in making calculations. The scales of measurement are very important because they determine the types of data analysis that can be performed. We should note that the nominal level is just used to classify data while the interval and ratio measurement levels are much more exact and more used for quantitative data analysis. After determining the measurement level, the next step in quantitative data analysis is to enter the data into a spreadsheet and organize it or to “code” in some way that will give meaning to data. | 4,422 | 5,617 |
msmarco_v2.1_doc_01_1668465060#17_2446824526 | http://intellspot.com/qualitative-vs-quantitative-data/ | Qualitative vs Quantitative Data: Analysis, Definitions, Examples | Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| Ratio – not only show order and have equal intervals, but they can also have a value of zero. Identifying the levels of measurement where a dataset falls under, will help you decide whether or not the data is useful in making calculations. The scales of measurement are very important because they determine the types of data analysis that can be performed. We should note that the nominal level is just used to classify data while the interval and ratio measurement levels are much more exact and more used for quantitative data analysis. After determining the measurement level, the next step in quantitative data analysis is to enter the data into a spreadsheet and organize it or to “code” in some way that will give meaning to data. The best way of doing that is with specialized data software. As you have the raw data, you cannot just sit and look at it. You need to take actions to identify some patterns or to visualize what the data is showing. This is where descriptive statistics and inferential statistics come to play. Step 2: | 4,879 | 5,920 |
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| The best way of doing that is with specialized data software. As you have the raw data, you cannot just sit and look at it. You need to take actions to identify some patterns or to visualize what the data is showing. This is where descriptive statistics and inferential statistics come to play. Step 2: Perform descriptive statistics
Descriptive statistics are used to describes and summarizes basic features of a data set. Commonly used descriptive statistics are: Central tendency (mean, mode, and median). Percentages. Dispersion (range, quartiles, variance, and standard deviation)
Distribution. | 5,617 | 6,217 |
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| Perform descriptive statistics
Descriptive statistics are used to describes and summarizes basic features of a data set. Commonly used descriptive statistics are: Central tendency (mean, mode, and median). Percentages. Dispersion (range, quartiles, variance, and standard deviation)
Distribution. Step 3: Perform inferential statistics
Inferential statistics are used to draw conclusions and trends about a large population based on a sample taken from it. Inferential statistics study the relationships between variables within a sample. Inferential statistics allow you to test different hypotheses and to generalize the gained results to the population as a whole. Key inferential techniques, methods, and types of calculations are: | 5,921 | 6,656 |
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| Step 3: Perform inferential statistics
Inferential statistics are used to draw conclusions and trends about a large population based on a sample taken from it. Inferential statistics study the relationships between variables within a sample. Inferential statistics allow you to test different hypotheses and to generalize the gained results to the population as a whole. Key inferential techniques, methods, and types of calculations are: Linear regression models
Logistic regression
Analysis of Variance (ANOVA)
Analysis of Covariance (ANCOVA)
Statistical significance (T-Test)
Correlation analysis
Step 4: Define statistical significance
Finally, you need to look for statistical significance. Statistical significance is captured through a ‘p-value’, which evaluate the probability that your discovering for the data are reliable results, not a coincidence. The lower the p-value, the more confident you can be that your findings are reliable. As you see when it comes to quantitative data analysis, there are many techniques and methods you can use. | 6,217 | 7,271 |
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| Linear regression models
Logistic regression
Analysis of Variance (ANOVA)
Analysis of Covariance (ANCOVA)
Statistical significance (T-Test)
Correlation analysis
Step 4: Define statistical significance
Finally, you need to look for statistical significance. Statistical significance is captured through a ‘p-value’, which evaluate the probability that your discovering for the data are reliable results, not a coincidence. The lower the p-value, the more confident you can be that your findings are reliable. As you see when it comes to quantitative data analysis, there are many techniques and methods you can use. The next step in our post for the difference between qualitative and quantitative data is to see what qualitative data analysis involves. Qualitative Data Analysis: Definition, steps, and types
It is harder to perform Qualitative Data Analysis (QDA) in comparison with quantitative one. QDA includes the processes and methods for analyzing data and providing some level of understanding, explanation, and interpretation of patterns and themes in textual data. Qualitative data analysis is very important because it allows data sciences and statisticians to form parameters for observing and analyzing larger sets of data. | 6,656 | 7,893 |
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| The next step in our post for the difference between qualitative and quantitative data is to see what qualitative data analysis involves. Qualitative Data Analysis: Definition, steps, and types
It is harder to perform Qualitative Data Analysis (QDA) in comparison with quantitative one. QDA includes the processes and methods for analyzing data and providing some level of understanding, explanation, and interpretation of patterns and themes in textual data. Qualitative data analysis is very important because it allows data sciences and statisticians to form parameters for observing and analyzing larger sets of data. For example, if a company need to identify the diversity of its personnel, it would look at qualitative data such as ethnicity and race of its employees. For comparison, quantitative data, in this case, could be the frequency of workers to belong to those ethnicities and races. In general, the qualitative data analysis has the following steps: Step 1: Become familiar with your data
As a data scientist or researcher, you have to read and re-read the data, record detailed notes and impressions, and deciding which pieces of data possess value. | 7,271 | 8,440 |
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Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| For example, if a company need to identify the diversity of its personnel, it would look at qualitative data such as ethnicity and race of its employees. For comparison, quantitative data, in this case, could be the frequency of workers to belong to those ethnicities and races. In general, the qualitative data analysis has the following steps: Step 1: Become familiar with your data
As a data scientist or researcher, you have to read and re-read the data, record detailed notes and impressions, and deciding which pieces of data possess value. Step 2: Define the key questions that they need to answer through the QDA
Each QDA has specific questions, problems or topics. Find out which questions do you need to answer. Step 3: Reduce and code the data into themes
This means to create categories and subcategories. | 7,893 | 8,711 |
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| Step 2: Define the key questions that they need to answer through the QDA
Each QDA has specific questions, problems or topics. Find out which questions do you need to answer. Step 3: Reduce and code the data into themes
This means to create categories and subcategories. These categories are very likely to get bigger as you work through your data. The list of build themes represents your first set of codes. Step 4: Search for patterns and connections
This step involves looking for the relative importance of data, identifying relationships between data sets or themes, and trying to find explanations from the available data. Step 5: | 8,440 | 9,078 |
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Qualitative vs Quantitative Data: Definitions, Analysis, Examples
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| These categories are very likely to get bigger as you work through your data. The list of build themes represents your first set of codes. Step 4: Search for patterns and connections
This step involves looking for the relative importance of data, identifying relationships between data sets or themes, and trying to find explanations from the available data. Step 5: Interpret the data and draw conclusions
After you identify the themes, connections, and patterns, now you need to assign meaning and importance to the data. It is very likely to find out much more than you could need, so you will have to decide what is most significant data and results. Note: qualitative data do not drive conclusions and generalizations across a population. This is an important difference between qualitative and quantitative data analysis. | 8,712 | 9,539 |
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| Interpret the data and draw conclusions
After you identify the themes, connections, and patterns, now you need to assign meaning and importance to the data. It is very likely to find out much more than you could need, so you will have to decide what is most significant data and results. Note: qualitative data do not drive conclusions and generalizations across a population. This is an important difference between qualitative and quantitative data analysis. In contrast, quantitative analysis can lead to conclusions or trends about a large population based on a sample taken from it. There is a range of approaches to qualitative data analysis. Some of the key approaches are: Content analysis – a technique to make inferences by interpreting and coding textual information (e.g., documents, graphics, oral communications). Thematic analysis – a widely-used QDA method that involves grouping the data into themes to d | 9,079 | 10,000 |
msmarco_v2.1_doc_01_1668477391#0_2446839257 | http://intellspot.com/root-cause-analysis-tools/ | Best Root Cause Analysis Tools and Techniques: Defined | Best Root Cause Analysis Tools and Methods
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| Best Root Cause Analysis Tools and Techniques: Defined
Best Root Cause Analysis Tools and Methods
You know that looking at symptoms of a problem is not enough to resolve it. You need to strike at the core of a problem by finding its key and root causes. This is where the root cause analysis tools and techniques come to help businesses resolve the situation by finding the best possible solutions. On this page: What is the root cause analysis (RCA)? Definition. Top 5 RCA tools and methods in use nowadays (The 5 Whys, Fishbone Diagram, Is/Is Not Analysis, FMEA, Affinity Diagram). As the name suggests, root cause analysis is a way for identifying the key causes of an event. The goal is to be found and implemented the most effective solutions. | 0 | 748 |
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| What is the root cause analysis (RCA)? Definition. Top 5 RCA tools and methods in use nowadays (The 5 Whys, Fishbone Diagram, Is/Is Not Analysis, FMEA, Affinity Diagram). As the name suggests, root cause analysis is a way for identifying the key causes of an event. The goal is to be found and implemented the most effective solutions. It’s commonly used when the things go wrong, but can also be used when the things go very well. RCA can be applied to almost any kind of problem that businesses face every day. From manufacturing problems to incorrect customer shipments, RCA applications are endless and can result in significant improvements in the business processes. There are a lot of tools and methods that may be used during a Root Cause Analysis. Some of them can be completed by one person, but in most cases, a team approach is the right one. | 412 | 1,267 |
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| It’s commonly used when the things go wrong, but can also be used when the things go very well. RCA can be applied to almost any kind of problem that businesses face every day. From manufacturing problems to incorrect customer shipments, RCA applications are endless and can result in significant improvements in the business processes. There are a lot of tools and methods that may be used during a Root Cause Analysis. Some of them can be completed by one person, but in most cases, a team approach is the right one. Let’s see the most popular root cause analysis tools in use today: The 5 Whys
As you might guess, The 5 Why method means you asking the question “Why”. You have to ask “Why” as many times as needed until you pass all the symptoms of a problem and get to the root cause. Commonly, the answer to the first “why” should suggest to another “why” and the answer to the second “why” will suggest to another and so on. The Five Whys is a simple RCS tool and technique that help you to fast determine the root cause of a situation. | 748 | 1,791 |
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| Let’s see the most popular root cause analysis tools in use today: The 5 Whys
As you might guess, The 5 Why method means you asking the question “Why”. You have to ask “Why” as many times as needed until you pass all the symptoms of a problem and get to the root cause. Commonly, the answer to the first “why” should suggest to another “why” and the answer to the second “why” will suggest to another and so on. The Five Whys is a simple RCS tool and technique that help you to fast determine the root cause of a situation. It’s simple and very easy to apply. The Five Whys is most useful when the problem involves human factors and interactions. Although this method is called “5 Whys,” there are many situations where you will need to ask the question fewer or more times than five before you find the core reasons for the problem. This technique produces linear regression models and sets of casual relationships and uses the experience of the problem owner to identify the key cause and possible solutions. Fishbone Diagram
Also known as Cause–and–Effect Diagram and Ishikawa Diagram, Fishbone is one of the most popular root cause analysis tools and methods out there. | 1,267 | 2,441 |
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| It’s simple and very easy to apply. The Five Whys is most useful when the problem involves human factors and interactions. Although this method is called “5 Whys,” there are many situations where you will need to ask the question fewer or more times than five before you find the core reasons for the problem. This technique produces linear regression models and sets of casual relationships and uses the experience of the problem owner to identify the key cause and possible solutions. Fishbone Diagram
Also known as Cause–and–Effect Diagram and Ishikawa Diagram, Fishbone is one of the most popular root cause analysis tools and methods out there. It identifies many possible causes for a problem. This diagram-based technique that involves Brainstorming and a visual display of many potential causes for a given problem. In a fishbone diagram, the causes are grouped into categories. These categories are brainstormed by the team. Typical categories include equipment, materials, processes or methods, measurements, environment, and people. | 1,792 | 2,835 |
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| It identifies many possible causes for a problem. This diagram-based technique that involves Brainstorming and a visual display of many potential causes for a given problem. In a fishbone diagram, the causes are grouped into categories. These categories are brainstormed by the team. Typical categories include equipment, materials, processes or methods, measurements, environment, and people. This type of root cause analysis aims to understand the possible causes by asking questions such as “what happened,” “where,” “when,”“why,” “how,”. The questions are asked until a possible cause is identified and the consequences are found for each category. This RCA tool is very useful when you’re trying to solve complicated and complex problems. More for Fishbone diagram you can find on the ACQ page. Is/Is Not Analysis
Is/Is Not Analysis is a simple but very powerful tool for root cause analysis used to understand the problem and the scope of it. | 2,441 | 3,390 |
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| This type of root cause analysis aims to understand the possible causes by asking questions such as “what happened,” “where,” “when,”“why,” “how,”. The questions are asked until a possible cause is identified and the consequences are found for each category. This RCA tool is very useful when you’re trying to solve complicated and complex problems. More for Fishbone diagram you can find on the ACQ page. Is/Is Not Analysis
Is/Is Not Analysis is a simple but very powerful tool for root cause analysis used to understand the problem and the scope of it. This analysis answers the questions what was and what was not made in order to produce the effect. It is often used in combination with other quality management tools such as 5 Whys and Fishbone analysis. The Is-Is Not analysis allows you to think about the problem and the boundaries of what it is or is not. Thus the tool helps you maintain your focus. It is crucial to define the boundary of the problem otherwise you may stray off the path and work on solving meaningless problems. | 2,835 | 3,876 |
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| This analysis answers the questions what was and what was not made in order to produce the effect. It is often used in combination with other quality management tools such as 5 Whys and Fishbone analysis. The Is-Is Not analysis allows you to think about the problem and the boundaries of what it is or is not. Thus the tool helps you maintain your focus. It is crucial to define the boundary of the problem otherwise you may stray off the path and work on solving meaningless problems. The analysis is followed by the ” What Is and Is Not” document that is a part of the characteristic of the problem. The process goes by asking the team different types of questions such as: “ Who is influenced by this problem?”, “ What do we know about the problem?”, “ Will we actually can do something?” | 3,391 | 4,179 |
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| The analysis is followed by the ” What Is and Is Not” document that is a part of the characteristic of the problem. The process goes by asking the team different types of questions such as: “ Who is influenced by this problem?”, “ What do we know about the problem?”, “ Will we actually can do something?” and etc. Asking the questions last until there is a clear definition of the problem and its scope. This analysis is used when a problem is being identified to decide what is in scope and what is not important at this time. Affinity Diagram
The Affinity Diagram, also known as a KJ diagram, is a part of Seven Management and Planning Tools, invented for organizing a lot of ideas and data. As one of the root cause analysis tools, it is used to generate and organize information relevant to the issue in question. | 3,876 | 4,692 |
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| and etc. Asking the questions last until there is a clear definition of the problem and its scope. This analysis is used when a problem is being identified to decide what is in scope and what is not important at this time. Affinity Diagram
The Affinity Diagram, also known as a KJ diagram, is a part of Seven Management and Planning Tools, invented for organizing a lot of ideas and data. As one of the root cause analysis tools, it is used to generate and organize information relevant to the issue in question. It is it is typically used directly after brainstorming to sort large numbers of ideas and possible causes of a problem into groups. The Affinity Diagram allows you to represent the structure of big and complex factors which impact a problem or a situation. Also, it splits these factors into smaller groups (according to their similarity) and helps teams to identify the major causes. An affinity diagram should be used to encourage discussion about a problem, seeing the patterns and identifying possible solutions or improvements. This analysis is used when a problem is large and complex and includes a lot of factors and causes. | 4,180 | 5,326 |
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| It is it is typically used directly after brainstorming to sort large numbers of ideas and possible causes of a problem into groups. The Affinity Diagram allows you to represent the structure of big and complex factors which impact a problem or a situation. Also, it splits these factors into smaller groups (according to their similarity) and helps teams to identify the major causes. An affinity diagram should be used to encourage discussion about a problem, seeing the patterns and identifying possible solutions or improvements. This analysis is used when a problem is large and complex and includes a lot of factors and causes. Failure Mode and Effects Analysis (FMEA)
Failure Mode and Effects Analysis is a structured approach for evaluating a process to identify potential failures that may exist within the design of a product or a process. Failure modes are the directions in which a process can fail. Effects are the ways that the failures can lead to bad outcomes. FMEA aims to define and limit these failure modes. FMEA is one of root cause analysis tools with a systematic approach, created with the help of a spreadsheet. | 4,693 | 5,829 |
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| Failure Mode and Effects Analysis (FMEA)
Failure Mode and Effects Analysis is a structured approach for evaluating a process to identify potential failures that may exist within the design of a product or a process. Failure modes are the directions in which a process can fail. Effects are the ways that the failures can lead to bad outcomes. FMEA aims to define and limit these failure modes. FMEA is one of root cause analysis tools with a systematic approach, created with the help of a spreadsheet. It allows you to anticipate what might go wrong with a product or process. FMEA helps to define the possible causes of failures. Used by many businesses, FMEA is one of the best ways of analyzing potential problems early in the development stage, making it easier for you to take quick action and soften the failure. Conclusion: Root cause analysis tools and techniques aim to improve products and processes. | 5,326 | 6,238 |
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| It allows you to anticipate what might go wrong with a product or process. FMEA helps to define the possible causes of failures. Used by many businesses, FMEA is one of the best ways of analyzing potential problems early in the development stage, making it easier for you to take quick action and soften the failure. Conclusion: Root cause analysis tools and techniques aim to improve products and processes. They allow you to find out why your projects are not what were expected to be. Each one of the above tools can be combined with one or more other RCA tools depending on the situation. Combining these tools is often necessary and very important. Although the most root cause analysis methods and techniques have the expected results if they are properly applied, it is crucial to make sure the team knows how to use and apply them. About The Author
Silvia Valcheva
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. | 5,830 | 6,813 |
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| They allow you to find out why your projects are not what were expected to be. Each one of the above tools can be combined with one or more other RCA tools depending on the situation. Combining these tools is often necessary and very important. Although the most root cause analysis methods and techniques have the expected results if they are properly applied, it is crucial to make sure the team knows how to use and apply them. 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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msmarco_v2.1_doc_01_1668485055#0_2446858543 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| What Does a Scatter Plot Show? What is The Purpose Of It? What Does a Scatter Plot Show? If you are wondering what does a scatter plot show, the answer is more simple than you might think. The scatter plot has also other names such as scatter diagram, scatter graph, and correlation chart. Scatter plot helps in many areas of today world – business, biology, social statistics, data science and etc. On this page: What is scatter plot? Definition. What is the purpose of a scatter plot? | 0 | 486 |
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| Scatter plot helps in many areas of today world – business, biology, social statistics, data science and etc. On this page: What is scatter plot? Definition. What is the purpose of a scatter plot? When to use it? Types of correlation in a scatter plot. Advantages and disadvantages. Let’s define it! It is an X-Y diagram that shows a relationship between two variables . | 289 | 660 |
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| When to use it? Types of correlation in a scatter plot. Advantages and disadvantages. Let’s define it! It is an X-Y diagram that shows a relationship between two variables . It is used to plot data points on a vertical and a horizontal axis. The purpose is to show how much one variable affects another. Example: A classic example is the relationship between monthly sales and advertising dollars in a company. The below table presents data for 7 online stores, their monthly e-commerce sales, and online advertising costs for the last year. | 486 | 1,028 |
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| It is used to plot data points on a vertical and a horizontal axis. The purpose is to show how much one variable affects another. Example: A classic example is the relationship between monthly sales and advertising dollars in a company. The below table presents data for 7 online stores, their monthly e-commerce sales, and online advertising costs for the last year. Online
Store
Monthly E-commerce Sales
(in 1000 s)
Online Advertising Dollars (1000 s)
1
368
1.7
2
340
1.5
3
665
2.8
4
954
5
5
331
1.3
6
556
2.2
7
376
1.3
Now, let’s create the scatter diagram based on the data we have. The scatter plot shows that there is a relationship between monthly e-commerce sales (Y) and online advertising costs (X). More advertising costs lead to more sales. The orange line you see in the plot is called “ line of best fit ” or a “trend line”. This line is used to help us make predictions that are based on past data. | 661 | 1,574 |
msmarco_v2.1_doc_01_1668485055#4_2446862328 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Online
Store
Monthly E-commerce Sales
(in 1000 s)
Online Advertising Dollars (1000 s)
1
368
1.7
2
340
1.5
3
665
2.8
4
954
5
5
331
1.3
6
556
2.2
7
376
1.3
Now, let’s create the scatter diagram based on the data we have. The scatter plot shows that there is a relationship between monthly e-commerce sales (Y) and online advertising costs (X). More advertising costs lead to more sales. The orange line you see in the plot is called “ line of best fit ” or a “trend line”. This line is used to help us make predictions that are based on past data. Usually, when there is a relationship between 2 variables, the first one is called independent. The second variable is called dependent because its values depend on the first variable. But it is also possible to have no relationship between 2 variables at all. So, What is The Purpose of a Scatter Plot? In today world of data science, Scatter graphs have a couple of purposes. | 1,028 | 1,952 |
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| Usually, when there is a relationship between 2 variables, the first one is called independent. The second variable is called dependent because its values depend on the first variable. But it is also possible to have no relationship between 2 variables at all. So, What is The Purpose of a Scatter Plot? In today world of data science, Scatter graphs have a couple of purposes. Let’s list them: To show whether 2 variables are related or not. To show how much one variable affects another – the main purpose! To help you predict the behavior of one variable (dependent) based on the measure of the other variable (independent). When To Use A Scatter Plot? | 1,574 | 2,230 |
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| Let’s list them: To show whether 2 variables are related or not. To show how much one variable affects another – the main purpose! To help you predict the behavior of one variable (dependent) based on the measure of the other variable (independent). When To Use A Scatter Plot? Scatter diagram has many applications and usages nowadays. Here are some of them: When trying to find out whether there is a relationship between 2 variables. When having paired numerical data. When working with root cause analysis tools to identify the potential for problems. | 1,953 | 2,508 |
msmarco_v2.1_doc_01_1668485055#7_2446865591 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Scatter diagram has many applications and usages nowadays. Here are some of them: When trying to find out whether there is a relationship between 2 variables. When having paired numerical data. When working with root cause analysis tools to identify the potential for problems. When just want to visualize the correlation between 2 large datasets without regard to time. Types of Correlation in a Scatter Plot
In the above text, we many times mentioned the relationship between 2 variables. Thi is called correlation. Ther are 3 types of correlation: 1. | 2,230 | 2,784 |
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| When just want to visualize the correlation between 2 large datasets without regard to time. Types of Correlation in a Scatter Plot
In the above text, we many times mentioned the relationship between 2 variables. Thi is called correlation. Ther are 3 types of correlation: 1. Positive Correlation
When one variable (dependent variable) increase as the other variable (independent variable) increases, there is a positive correlation. Height and clothes size is a good example here. When the height of a child increase, the clothes size also increase. Another common example is the correlation between height and weight. Visually, the positive correlation looks like that: | 2,508 | 3,180 |
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| Positive Correlation
When one variable (dependent variable) increase as the other variable (independent variable) increases, there is a positive correlation. Height and clothes size is a good example here. When the height of a child increase, the clothes size also increase. Another common example is the correlation between height and weight. Visually, the positive correlation looks like that: As you see in the positive correlation, the “best-fit line” goes from the origin out to high Y- and X- values. 2. Negative correlation
As you might guess, we have negative correlation when the increase of one variable leads to decrease in the other. Car age and car price are correlating negatively. Usually, when car age increase, the car price decrease. | 2,785 | 3,536 |
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| As you see in the positive correlation, the “best-fit line” goes from the origin out to high Y- and X- values. 2. Negative correlation
As you might guess, we have negative correlation when the increase of one variable leads to decrease in the other. Car age and car price are correlating negatively. Usually, when car age increase, the car price decrease. Let’s see how the Scatter plot looks like: As you see in the negative correlation, the trend line goes from a high-value on the y-axis down to a high-value on the x-axis. 3. No correlation
No correlation means there is no relationship between the variables. For example, there is no correlation between a child’ clothes size and his/her grades at school. | 3,180 | 3,891 |
msmarco_v2.1_doc_01_1668485055#11_2446869726 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Let’s see how the Scatter plot looks like: As you see in the negative correlation, the trend line goes from a high-value on the y-axis down to a high-value on the x-axis. 3. No correlation
No correlation means there is no relationship between the variables. For example, there is no correlation between a child’ clothes size and his/her grades at school. A Scatter graph without correlation looks like that: The above graphs are made by www.meta-chart.com/
Scatter plots aren’t one of the most often used visualization type of charts, but they have an important role. They show you large quantities of data and present a correlation between variables. In addition to that, they are a valuable tool for working with linear regression models. As everything else in this world, Scatter plots have some pros and cons: | 3,536 | 4,350 |
msmarco_v2.1_doc_01_1668485055#12_2446870910 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| A Scatter graph without correlation looks like that: The above graphs are made by www.meta-chart.com/
Scatter plots aren’t one of the most often used visualization type of charts, but they have an important role. They show you large quantities of data and present a correlation between variables. In addition to that, they are a valuable tool for working with linear regression models. As everything else in this world, Scatter plots have some pros and cons: Advantages of Scatter plots: Show a relationship and a trend in the data relationship. Show all data points, including minimum and maximum and outliers. Can highlight correlations. Retains the exact data values and sample size. | 3,891 | 4,578 |
msmarco_v2.1_doc_01_1668485055#13_2446871956 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Advantages of Scatter plots: Show a relationship and a trend in the data relationship. Show all data points, including minimum and maximum and outliers. Can highlight correlations. Retains the exact data values and sample size. Shows both positive and negative type of graphical correlation. Disadvantages of Scatter Plots: Flat best-fit line gives inconclusive results. Interpretation can be subjective. Correlation does not mean and not show causation. | 4,350 | 4,805 |
msmarco_v2.1_doc_01_1668485055#14_2446872764 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Shows both positive and negative type of graphical correlation. Disadvantages of Scatter Plots: Flat best-fit line gives inconclusive results. Interpretation can be subjective. Correlation does not mean and not show causation. Data on both axes have to be continuous data (see our post discrete vs continuous data ). You cannot use Scatter diagrams to show the relation of more than two variables. It is true that Scatter plots have some limitations. However, when used correctly, they are a great tool for overviews and showing patterns and relationship between some datasets. If you need some real-life examples of how Scatter charts work, check our post simple linear regression examples. | 4,578 | 5,270 |
msmarco_v2.1_doc_01_1668485055#15_2446873809 | http://intellspot.com/scatter-plot/ | What Does a Scatter Plot Show? What is The Purpose Of It? | What Does a Scatter Plot Show?
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| Data on both axes have to be continuous data (see our post discrete vs continuous data ). You cannot use Scatter diagrams to show the relation of more than two variables. It is true that Scatter plots have some limitations. However, when used correctly, they are a great tool for overviews and showing patterns and relationship between some datasets. If you need some real-life examples of how Scatter charts work, check our post simple linear regression 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. | 4,805 | 5,699 |
msmarco_v2.1_doc_01_1668491217#0_2446875060 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Easy and Simple Database Software Programs: List
Simple Database Software Programs: List
There are many benefits that an easy to use and simple database software program can bring to your business. In the first place, a simple database system makes the whole process of creating, managing, and storing your data, faster and effortless. Dozens of database management programs and apps are available on the market: for download for Mac, Windows, Linux, Android or online database software tools. When it comes to easiest database creators, the majority of them are for personal needs, small business and mid-size companies (such as simple sale and customer database systems or relational database creator). Here, we collected a comprehensive list of the simplest databases management solutions. 1. Database Oasis
Database Oasis is a popular solution that allows you to create and custom databases in minutes. | 0 | 906 |
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| for download for Mac, Windows, Linux, Android or online database software tools. When it comes to easiest database creators, the majority of them are for personal needs, small business and mid-size companies (such as simple sale and customer database systems or relational database creator). Here, we collected a comprehensive list of the simplest databases management solutions. 1. Database Oasis
Database Oasis is a popular solution that allows you to create and custom databases in minutes. Absolutely no coding required ! The program allows you to get and stay organized as gives you access to all of your data in one easy to use list. In addition, it’s very easy to share your data and information with others. All of your reports can be printed, posted to a web page or automatically attached to an email. Database Oasis provides an advanced functionality but still keeps it simple. | 413 | 1,301 |
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| Absolutely no coding required ! The program allows you to get and stay organized as gives you access to all of your data in one easy to use list. In addition, it’s very easy to share your data and information with others. All of your reports can be printed, posted to a web page or automatically attached to an email. Database Oasis provides an advanced functionality but still keeps it simple. Supported Operating Systems: for Windows. Pricing: paid basic and professional editions. Website: | 907 | 1,399 |
msmarco_v2.1_doc_01_1668491217#3_2446878476 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Supported Operating Systems: for Windows. Pricing: paid basic and professional editions. Website: https://databaseoasis.com
2. Amazon SimpleDB
Another super popular solid but simple database software solution. It is a highly available NoSQL data store that offloads the work of database administration. It handles the core database functions of data indexing and querying in the cloud. Amazon SimpleDB offers a simple web services interface to create and store multiple data sets, query your data easily, and return the results. | 1,302 | 1,830 |
msmarco_v2.1_doc_01_1668491217#4_2446879380 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| https://databaseoasis.com
2. Amazon SimpleDB
Another super popular solid but simple database software solution. It is a highly available NoSQL data store that offloads the work of database administration. It handles the core database functions of data indexing and querying in the cloud. Amazon SimpleDB offers a simple web services interface to create and store multiple data sets, query your data easily, and return the results. In addition, your data is automatically indexed. It makes it easy to fastly find the information you want. Pricing: based on your actual usage. Plus it provides a free tier. | 1,400 | 2,004 |
msmarco_v2.1_doc_01_1668491217#5_2446880360 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| In addition, your data is automatically indexed. It makes it easy to fastly find the information you want. Pricing: based on your actual usage. Plus it provides a free tier. Website: https://aws.amazon.com/
3. Apache OpenOffice Base
As the name suggests it is an open source data management system. Apache OpenOffice Base is a fully featured desktop database program able to cover the needs of a wide range of users: from tracking personal information to producing a corporate monthly departmental sales reports. | 1,831 | 2,343 |
msmarco_v2.1_doc_01_1668491217#6_2446881248 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Website: https://aws.amazon.com/
3. Apache OpenOffice Base
As the name suggests it is an open source data management system. Apache OpenOffice Base is a fully featured desktop database program able to cover the needs of a wide range of users: from tracking personal information to producing a corporate monthly departmental sales reports. If you are a newbie to database design, the system has wizards to help you create Tables, Forms, Queries, and Reports with ease. It has also a set of predefined table definitions for tracking Customers, Sales Orders, Assets, Invoices and etc. Apache OpenOffice Base is available for Mac OS, Windows, and Linux. Pricing: Open Source, completely free of any license fees. | 2,004 | 2,713 |
msmarco_v2.1_doc_01_1668491217#7_2446882332 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| If you are a newbie to database design, the system has wizards to help you create Tables, Forms, Queries, and Reports with ease. It has also a set of predefined table definitions for tracking Customers, Sales Orders, Assets, Invoices and etc. Apache OpenOffice Base is available for Mac OS, Windows, and Linux. Pricing: Open Source, completely free of any license fees. Website: www.openoffice.org
4. Basemaster
Basemaster is an absolutely easy and simple to use tool for creating online databases and automating your small business. Truly intuitive and flexible software. Among its key features are: | 2,343 | 2,944 |
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| Website: www.openoffice.org
4. Basemaster
Basemaster is an absolutely easy and simple to use tool for creating online databases and automating your small business. Truly intuitive and flexible software. Among its key features are: Table Designer, Differentiation of access, Conducting Mailings, Generation of documents, Reports (with different types of graphs ), and Forms. A great option for mid and small businesses. Pricing: Free and paid plans for a monthly subscription. Website: | 2,713 | 3,198 |
msmarco_v2.1_doc_01_1668491217#9_2446884168 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Table Designer, Differentiation of access, Conducting Mailings, Generation of documents, Reports (with different types of graphs ), and Forms. A great option for mid and small businesses. Pricing: Free and paid plans for a monthly subscription. Website: https://basemaster.com
5. Knack
If your searching for simple database software with powerful features and outstanding support, Knack worth considering. It requires no coding . Knack provides you with all you need to transform your data into an online database in an easy way. With Knack, you can structure your data with data types like names and emails; | 2,945 | 3,553 |
msmarco_v2.1_doc_01_1668491217#10_2446885152 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| https://basemaster.com
5. Knack
If your searching for simple database software with powerful features and outstanding support, Knack worth considering. It requires no coding . Knack provides you with all you need to transform your data into an online database in an easy way. With Knack, you can structure your data with data types like names and emails; connect your data; extend your data with special options such as formulas and equations. Also, it is super easy to manage, share, and analyze your data. Pricing: 3 paid plans for a monthly subscription. | 3,199 | 3,756 |
msmarco_v2.1_doc_01_1668491217#11_2446886086 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| connect your data; extend your data with special options such as formulas and equations. Also, it is super easy to manage, share, and analyze your data. Pricing: 3 paid plans for a monthly subscription. Website: https://www.knack.com/
6. Sesame Database Manager
Whether you’re a small business, a corporate administrator, a professional application developer, or a person who wants to keep track of stuff, Sesame provides all you need to easily, rapidly create database applications. Sesame Database Manager is a program for download and runs in Windows XP/Vista/7/8/10 and Linux (Intel). It is a painless to use tool for newbies to databases and offers more advanced tools for those with more experience. | 3,554 | 4,259 |
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| Website: https://www.knack.com/
6. Sesame Database Manager
Whether you’re a small business, a corporate administrator, a professional application developer, or a person who wants to keep track of stuff, Sesame provides all you need to easily, rapidly create database applications. Sesame Database Manager is a program for download and runs in Windows XP/Vista/7/8/10 and Linux (Intel). It is a painless to use tool for newbies to databases and offers more advanced tools for those with more experience. The key features include centralized design facilities, a consistent form-based interface, extensive and powerful search facilities, universally portable HTML (web-ready) reports, multiple forms and many others. Pricing: Paid personal and business packages. Website: http://sesamedatabase.com
7. | 3,756 | 4,555 |
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| The key features include centralized design facilities, a consistent form-based interface, extensive and powerful search facilities, universally portable HTML (web-ready) reports, multiple forms and many others. Pricing: Paid personal and business packages. Website: http://sesamedatabase.com
7. Restdb.io
Restdb.io is one of the easiest to use web-based NoSQL database programs designed for speed and simplicity. The data management application, schema and REST API are instantly available. Some of its core features are: supports the most common data types (like text and numbers); access and collaboration from any device; | 4,259 | 4,885 |
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| Restdb.io
Restdb.io is one of the easiest to use web-based NoSQL database programs designed for speed and simplicity. The data management application, schema and REST API are instantly available. Some of its core features are: supports the most common data types (like text and numbers); access and collaboration from any device; role-based access control; random data generator; built for the modern Web. Pricing: Free and paid plans for a monthly subscription. | 4,556 | 5,018 |
msmarco_v2.1_doc_01_1668491217#15_2446890194 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| role-based access control; random data generator; built for the modern Web. Pricing: Free and paid plans for a monthly subscription. Website: https://restdb.io/
8. Pakker
For those who want to create, manage and share data in real-time from everywhere without any programming, Pakker might be a solution. With this easy to use program, you can create online databases in a few clicks and share it with others. Pakker allows you to design databases with intuitive drag-drop visual designer, include text, images, videos, files and many more. | 4,886 | 5,426 |
msmarco_v2.1_doc_01_1668491217#16_2446891111 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Website: https://restdb.io/
8. Pakker
For those who want to create, manage and share data in real-time from everywhere without any programming, Pakker might be a solution. With this easy to use program, you can create online databases in a few clicks and share it with others. Pakker allows you to design databases with intuitive drag-drop visual designer, include text, images, videos, files and many more. You are able to collaborate in real-time, link different data records, automate data calculation and etc. Organize and share everything you want – your contacts, invoices, customers, sales orders, recipes, inventories, and etc. One of the easiest tools for managing data. Pricing: Free solution for Community and paid monthly subscription plans. | 5,018 | 5,772 |
msmarco_v2.1_doc_01_1668491217#17_2446892246 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| You are able to collaborate in real-time, link different data records, automate data calculation and etc. Organize and share everything you want – your contacts, invoices, customers, sales orders, recipes, inventories, and etc. One of the easiest tools for managing data. Pricing: Free solution for Community and paid monthly subscription plans. Website: https://www.pakker.io/
9. Ragic
Ragic is an absolutely simple cloud database management software in a spreadsheet style. This online database creator enables the business of all sizes to build relational databases without any coding and programming skills. Use as many tables and forms as you want to manage your data with no effort. | 5,427 | 6,115 |
msmarco_v2.1_doc_01_1668491217#18_2446893316 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Website: https://www.pakker.io/
9. Ragic
Ragic is an absolutely simple cloud database management software in a spreadsheet style. This online database creator enables the business of all sizes to build relational databases without any coding and programming skills. Use as many tables and forms as you want to manage your data with no effort. You get powerful features without a line of code: access from Mobile, search & query, controlled access, build relations between sheets, clear data visualization and reports, calendars, reminders and many others. Pricing: free, lite, professional, on-premise and Enterprise solutions. Website: | 5,772 | 6,409 |
msmarco_v2.1_doc_01_1668491217#19_2446894329 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| You get powerful features without a line of code: access from Mobile, search & query, controlled access, build relations between sheets, clear data visualization and reports, calendars, reminders and many others. Pricing: free, lite, professional, on-premise and Enterprise solutions. Website: www.ragic.com
10. Kohezion
Kohezion is a truly simple database software solution that allows you to create your own online databases in a few easy steps. No programming or special knowledge required. Kohezion gives you the power to collaborate and to share with your team, automate your reports, and upload all your data from different sources fast and easy. It is a secure and reliable tool that lets you manage and customize your data to your own needs. | 6,115 | 6,865 |
msmarco_v2.1_doc_01_1668491217#20_2446895455 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| www.ragic.com
10. Kohezion
Kohezion is a truly simple database software solution that allows you to create your own online databases in a few easy steps. No programming or special knowledge required. Kohezion gives you the power to collaborate and to share with your team, automate your reports, and upload all your data from different sources fast and easy. It is a secure and reliable tool that lets you manage and customize your data to your own needs. Pricing: Free and paid plans. Website: https://www.kohezion.com
Want more simple database software programs? Here is a list of some other good and very easy to use solutions: | 6,410 | 7,040 |
msmarco_v2.1_doc_01_1668491217#21_2446896463 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Pricing: Free and paid plans. Website: https://www.kohezion.com
Want more simple database software programs? Here is a list of some other good and very easy to use solutions: 11. Sodadb (Simple Online Database) – a new approach to online databases. ( https://sodadb.com)
12. Kirix – easy to use, has the power you need to work with large files and helps you get your work done faster. ( www.kirix.com)
13. | 6,865 | 7,271 |
msmarco_v2.1_doc_01_1668491217#22_2446897256 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| 11. Sodadb (Simple Online Database) – a new approach to online databases. ( https://sodadb.com)
12. Kirix – easy to use, has the power you need to work with large files and helps you get your work done faster. ( www.kirix.com)
13. Memento Database – flexible and easy to use database manager for Android & Desktop. ( https://mementodatabase.com)
14. Brilliant Database – you can develop any database application without the need for any special knowledge or skills. ( www.brilliantdatabase.com)
15. My Visual Database – another simple development environment databases, without the need for specialists and programming skills. | 7,040 | 7,667 |
msmarco_v2.1_doc_01_1668491217#23_2446898286 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Memento Database – flexible and easy to use database manager for Android & Desktop. ( https://mementodatabase.com)
14. Brilliant Database – you can develop any database application without the need for any special knowledge or skills. ( www.brilliantdatabase.com)
15. My Visual Database – another simple development environment databases, without the need for specialists and programming skills. ( http://myvisualdatabase.com)
16. Axisbase – a popular database system to track whatever kind of information your business deals with. ( www.axisbase.com)
17. SpeedBase Professional Database – simple database software with a comprehensive range of options to build your own database adjusted to your own needs. ( www.infolinesoftware.com)
18. | 7,272 | 8,011 |
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| ( http://myvisualdatabase.com)
16. Axisbase – a popular database system to track whatever kind of information your business deals with. ( www.axisbase.com)
17. SpeedBase Professional Database – simple database software with a comprehensive range of options to build your own database adjusted to your own needs. ( www.infolinesoftware.com)
18. Couchbase Server – powerful and easy to use NoSQL database. ( www.couchbase.com)
19. Microsoft Access – you know this solution. ( www.microsoft.com)
20. File Amigo – an absolutely easy and free software to manage data your way. | 7,667 | 8,239 |
msmarco_v2.1_doc_01_1668491217#25_2446900406 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| Couchbase Server – powerful and easy to use NoSQL database. ( www.couchbase.com)
19. Microsoft Access – you know this solution. ( www.microsoft.com)
20. File Amigo – an absolutely easy and free software to manage data your way. ( www.fileamigo.com)
If you are searching for data management solutions, then our posts “best open source data modeling tools ” and “ best data cleansing software ” might help you. What is your suggestion for simple database software program? Share your thoughts with us. 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. | 8,012 | 8,832 |
msmarco_v2.1_doc_01_1668491217#26_2446901641 | http://intellspot.com/simple-database-software/ | Easy and Simple Database Software Programs: List | Simple Database Software Programs: List
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| ( www.fileamigo.com)
If you are searching for data management solutions, then our posts “best open source data modeling tools ” and “ best data cleansing software ” might help you. What is your suggestion for simple database software program? Share your thoughts with us. 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. | 8,239 | 8,940 |
msmarco_v2.1_doc_01_1668500655#0_2446902741 | http://intellspot.com/types-data-analysis/ | 10 Top Types of Data Analysis Methods and Techniques | 10 Key Types of Data Analysis Methods and Techniques
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| 10 Top Types of Data Analysis Methods and Techniques
10 Key Types of Data Analysis Methods and Techniques
Our modern information age leads to dynamic and extremely high growth of the data mining world. No doubt, that it requires adequate and effective different types of data analysis methods, techniques, and tools that can respond to constantly increasing business research needs. In fact, data mining does not have its own methods of data analysis. It uses the methodologies and techniques of other related areas of science. Among the methods used in small and big data analysis are: Mathematical and statistical techniques
Methods based on artificial intelligence, machine learning
Visualization and graphical method and tools
Here we will see a list of the most known classic and modern types of data analysis methods and models. Mathematical and Statistical Methods for Data Analysis
Mathematical and statistical sciences have much to give to data mining management and analysis. In fact, most data mining techniques are statistical data analysis tools. Some methods and techniques are well known and very effective. 1. | 0 | 1,125 |
msmarco_v2.1_doc_01_1668500655#1_2446904268 | http://intellspot.com/types-data-analysis/ | 10 Top Types of Data Analysis Methods and Techniques | 10 Key Types of Data Analysis Methods and Techniques
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| Mathematical and statistical techniques
Methods based on artificial intelligence, machine learning
Visualization and graphical method and tools
Here we will see a list of the most known classic and modern types of data analysis methods and models. Mathematical and Statistical Methods for Data Analysis
Mathematical and statistical sciences have much to give to data mining management and analysis. In fact, most data mining techniques are statistical data analysis tools. Some methods and techniques are well known and very effective. 1. Descriptive Analysis
Descriptive analysis is an insight into the past. This statistical technique does exactly what the name suggests -“Describe”. It looks at data and analyzes past events and situations for getting an idea of how to approach the future. Descriptive analytics looks at past/historical performance to understand the reasons behind past failure or success. It allows us to learn from past behaviors, and find out how they might influence future performance. | 586 | 1,598 |
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| Descriptive Analysis
Descriptive analysis is an insight into the past. This statistical technique does exactly what the name suggests -“Describe”. It looks at data and analyzes past events and situations for getting an idea of how to approach the future. Descriptive analytics looks at past/historical performance to understand the reasons behind past failure or success. It allows us to learn from past behaviors, and find out how they might influence future performance. 2. Regression Analysis
Regression analysis allows modeling the relationship between a dependent variable and one or more independent variables. In data mining, this technique is used to predict the values, given a particular dataset. For example, regression might be used to predict the price of a product, when taking into consideration other variables. Regression is one of the most popular types of data analysis methods used in business, data-driven marketing, financial forecasting, etc. | 1,126 | 2,091 |
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| 2. Regression Analysis
Regression analysis allows modeling the relationship between a dependent variable and one or more independent variables. In data mining, this technique is used to predict the values, given a particular dataset. For example, regression might be used to predict the price of a product, when taking into consideration other variables. Regression is one of the most popular types of data analysis methods used in business, data-driven marketing, financial forecasting, etc. There is a huge range of different types of regression models such as linear regression models, multiple regression, logistic regression, ridge regression, nonlinear regression, life data regression, and many many others. 3. Factor Analysis
Factor analysis is a regression-based data analysis technique, used to find an underlying structure in a set of variables. It goes with finding new independent factors (variables) that describe the patterns and models of relationships among original dependent variables. Factor analysis is a very popular tool for researching variable relationships for complex topics such as psychological scales and socioeconomic status. | 1,598 | 2,755 |
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| There is a huge range of different types of regression models such as linear regression models, multiple regression, logistic regression, ridge regression, nonlinear regression, life data regression, and many many others. 3. Factor Analysis
Factor analysis is a regression-based data analysis technique, used to find an underlying structure in a set of variables. It goes with finding new independent factors (variables) that describe the patterns and models of relationships among original dependent variables. Factor analysis is a very popular tool for researching variable relationships for complex topics such as psychological scales and socioeconomic status. FA is a basic step towards effective clustering and classification procedures. 4. Dispersion Analysis
Dispersion analysis is not a so common method used in data mining but still has a role there. Dispersion is the spread to which a set of data is stretched. It is a technique of describing how extended a set of data is. | 2,091 | 3,076 |
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| FA is a basic step towards effective clustering and classification procedures. 4. Dispersion Analysis
Dispersion analysis is not a so common method used in data mining but still has a role there. Dispersion is the spread to which a set of data is stretched. It is a technique of describing how extended a set of data is. The measure of dispersion helps data scientists to study the variability of the things. Generally, the dispersion has two matters: first, it represents the variation of the things among themselves, and second, it represents the variation around the average value. If the difference between the value and average is significant, then the dispersion is high. Otherwise, it is low. | 2,755 | 3,455 |
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| The measure of dispersion helps data scientists to study the variability of the things. Generally, the dispersion has two matters: first, it represents the variation of the things among themselves, and second, it represents the variation around the average value. If the difference between the value and average is significant, then the dispersion is high. Otherwise, it is low. 5. Discriminant Analysis
Discriminant analysis is one of the most powerful classification techniques in data mining. The discriminant analysis utilizes variable measurements on different groups of items to underline points that distinguish the groups. These measurements are used to classify new items. Typical examples of this method uses are: | 3,076 | 3,800 |
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| 5. Discriminant Analysis
Discriminant analysis is one of the most powerful classification techniques in data mining. The discriminant analysis utilizes variable measurements on different groups of items to underline points that distinguish the groups. These measurements are used to classify new items. Typical examples of this method uses are: in classifying applications for credit cards into low risk and high-risk categories, classifying customers of new products into different groups, medical studies implicating alcoholics and non-alcoholics, and etc. 6. Time Series Analysis
You know that, in almost every scientific area, measurements are executed over time. These look-outs lead to a collection of organized data known as time series. A good example of time series is the daily value of a stock market index. | 3,455 | 4,274 |
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| in classifying applications for credit cards into low risk and high-risk categories, classifying customers of new products into different groups, medical studies implicating alcoholics and non-alcoholics, and etc. 6. Time Series Analysis
You know that, in almost every scientific area, measurements are executed over time. These look-outs lead to a collection of organized data known as time series. A good example of time series is the daily value of a stock market index. Time series data analysis is the process of modeling and explaining time-dependent series of data points. The goal is to draw all meaningful information (statistics, rules, and patterns) from the shape of data. Afterward, this information is used for creating and modeling forecasts that are able to predict future evolutions. Methods Based on The Artificial Intelligence, Machine Learning and Heuristic Algorithms
These modern methods attract the attention of data scientists with their extended capabilities and the ability to solve non-traditional tasks. In addition, they can be easily and efficiently implemented and performed by special software systems and tools. | 3,801 | 4,945 |
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| Time series data analysis is the process of modeling and explaining time-dependent series of data points. The goal is to draw all meaningful information (statistics, rules, and patterns) from the shape of data. Afterward, this information is used for creating and modeling forecasts that are able to predict future evolutions. Methods Based on The Artificial Intelligence, Machine Learning and Heuristic Algorithms
These modern methods attract the attention of data scientists with their extended capabilities and the ability to solve non-traditional tasks. In addition, they can be easily and efficiently implemented and performed by special software systems and tools. Here is a list of some of the most popular of these types of data analysis methods: 7. Artificial Neural Networks
No doubt that this is one of the most popular new and modern types of data analysis methods out there. According to http://neuralnetworksanddeeplearning.com ,”Neutral Networks are a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data”
Artificial Neural Networks (ANN), often just called a “neural network”, present a brain metaphor for information processing. These models are biologically inspired computational models. | 4,274 | 5,539 |
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