Pythonã§æ£è¦åå¸ã®å¹³åå¤ã®ä¿¡é ¼åºéãè¨ç®ããæ¹æ³ (2016/02/17) 説æ ãã¾ãã«ãåºæ¬çãªãã¨ãªã®ã ãããããä¸ã§æ¤ç´¢ãããééã£ãä¾ãæå¤ã¨æ²¢å±±è¦ã¤ãã£ãã®ã§ã以ä¸ã«æ£ããã¨æãããã³ã¼ããè¼ããã import numpy as np from scipy import stats n_samples = 100 alpha = 0.95 data = np.random.randn(n_samples) mean_val = np.mean(data) sem_val = stats.sem(data) # standared error of the mean ci = stats.t.interval(alpha, len(data)-1, loc=mean_val, scale=sem_val) print('mean:', mean_val) print('c
{{#tags}}- {{label}}
{{/tags}}