some small bug fix, especially the standard deviation algorithm

P102_roll_dice.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 
 import random
-#import numpy as np
+import numpy as np
 #import pandas as pd
 from matplotlib import pyplot as plt
 
@@ -11,22 +11,28 @@ def random_dice_roll():
 
 
 trials_list=[]
-std_deviation=0.0
+std_deviation_tmp=0.0
 
-num_trials=1000
+num_trials=100
 for trial in range(num_trials):
     trials_list.append (random_dice_roll())
 
 avg=sum(trials_list)/float(num_trials)
 
+print ('the trail list is shown as below:\n',trials_list)
+print ('the avergae dice roll point = ',avg)
+
 for trial in range(num_trials):
-    std_deviation+=(trials_list[trial]-avg)**2
+    std_deviation_tmp+=(trials_list[trial]-avg)**2
+
+std_deviation=(std_deviation_tmp/(num_trials-1))**0.5
+
+print ("\nnote: you shall be careful for the stdandard deviation calculation, bias (/n) or non-bias (/n-1)!!")
+print ('my calculated stdandard deviation (non-bias,/n-1) = ',std_deviation)
+print ('use numpy lib to calculate standard deviation directly (non-bias,/n-1) = ', np.std(trials_list, ddof=1))
 
-std_deviation=std_deviation/(num_trials-1)
 
-print (trials_list)
-print (avg)
-print (std_deviation)
+# another version, calculate standard deviation for various data list.
 
 '''
 num_trials=range(100,1000,10)

P38_data_sd_analysis.py

@@ -18,7 +18,7 @@
 
 print ('\n')
 
-sqrt_diff_list=[]
+diff_squre_list=[]
 
 num_items=len(temperature)
 product=1.
@@ -27,18 +27,18 @@
 
 for temp in temperature:
     diff=temp-mean_temp
-    sqrt_diff=diff**2
-    sqrt_diff_list.append(sqrt_diff)
-    average_sqrt_diff=np.mean(sqrt_diff_list)
+    diff_squre=diff**2
+    diff_squre_list.append(diff_squre)
+    average_diff_squre=np.mean(diff_squre_list)
     product*=temp
 
-standard_deviation = np.sqrt(average_sqrt_diff)
+standard_deviation = np.sqrt(average_diff_squre)
 geometric_mean = product ** (1./num_items)
 
-print ('Standard Deviation = ',standard_deviation)
+print ('Standard Deviation (bias, /n) = ',standard_deviation)
 
 print ('Geometric Mean = ',geometric_mean)
 
 print ('=======method-2 to calculate standard deviation, using numpy directly =======')
 
-print ('Standard Deviation = ',np.std(temperature))
+print ('Standard Deviation (bias, /n) = ',np.std(temperature))