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 an array.
I have access to numpy, statsmodel, pandas, and scipy (I think).
>>> 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