Probability to z-score and vice versa in python

问题:

I have numpy, statsmodel, pandas, and scipy(I think)

How do I calculate the z score of a p-value and vice versa?

For example if I have a p value of 0.95 I should get 1.96 in return.

I saw some functions in scipy but they only run a z-test on a array.

回答1:

>>> import scipy.stats as st >>> st.norm.ppf(.95) 1.6448536269514722 >>> st.norm.cdf(1.64) 0.94949741652589625 

As other users noted, Python calculates left/lower-tail probabilities by default. If you want to determine the density points where 95% of the distribution is included, you have to take another approach:

>>>st.norm.ppf(.975) 1.959963984540054 >>>st.norm.ppf(.025) -1.960063984540054 

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