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  1. import numpy as np
  2.  
  3. raw_data_points = np.array([ 53, 48, 40, 30, 30 ]) #spitballed based on the chart in Fig 19
  4.  
  5. sample_mean = np.mean( raw_data_points )
  6. sample_standard_deviation = np.std( raw_data_points )
  7. sample_std_err_of_mean = sample_standard_deviation / np.sqrt( len( raw_data_points ) )
  8. sample_95pcnt_interval = 1.96 * sample_std_err_of_mean
  9.  
  10. print "Confidence interval: ", sample_mean, "+-", sample_95pcnt_interval
Success #stdin #stdout 0.03s 83136KB
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Standard input is empty
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Confidence interval:  40.2 +- 8.15510755294
https://ideone.com/xSvVkD
language:
Python (cpython 2.7.16)
created:
7 years ago
visibility:
public

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