Haleshot commited on
Commit
39a7ead
·
unverified ·
1 Parent(s): 3ca922c
Files changed (1) hide show
  1. probability/11_expectation.py +0 -3
probability/11_expectation.py CHANGED
@@ -459,7 +459,6 @@ def _(
459
  formula = "E[X] = p"
460
 
461
  elif dist_selection.value == "binomial":
462
- # Get parameter range for visualization
463
  p_min, p_max = param_range.value
464
  param_values = np.linspace(p_min, p_max, 100)
465
 
@@ -473,7 +472,6 @@ def _(
473
  formula = f"E[X] = n × p = {n} × p"
474
 
475
  elif dist_selection.value == "geometric":
476
- # Get parameter range for visualization
477
  p_min, p_max = param_range.value
478
  # Ensure p is not 0 for geometric distribution
479
  p_min = max(0.01, p_min)
@@ -488,7 +486,6 @@ def _(
488
  formula = "E[X] = 1/p"
489
 
490
  else: # Poisson
491
- # Get parameter range for visualization
492
  lambda_min, lambda_max = lambda_range.value
493
  param_values = np.linspace(lambda_min, lambda_max, 100)
494
 
 
459
  formula = "E[X] = p"
460
 
461
  elif dist_selection.value == "binomial":
 
462
  p_min, p_max = param_range.value
463
  param_values = np.linspace(p_min, p_max, 100)
464
 
 
472
  formula = f"E[X] = n × p = {n} × p"
473
 
474
  elif dist_selection.value == "geometric":
 
475
  p_min, p_max = param_range.value
476
  # Ensure p is not 0 for geometric distribution
477
  p_min = max(0.01, p_min)
 
486
  formula = "E[X] = 1/p"
487
 
488
  else: # Poisson
 
489
  lambda_min, lambda_max = lambda_range.value
490
  param_values = np.linspace(lambda_min, lambda_max, 100)
491