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edited Mar 3, 2018 at 16:12You can use the ppf method (i.e. the quantile function) of scipy.stats.t:
In [129]: from scipy.stats import tIn [130]: alpha = 0.025In [131]: t.ppf(1 - alpha, df=9)Out[131]: 2.2621571627409915t.ppf() ultimately calls scipy.special.stdtrit, so you could also use that function and avoid the slight overhead of going through t.ppf():
In [141]: from scipy.special import stdtritIn [142]: alpha = 0.025In [143]: stdtrit(9, 1 - alpha)Out[143]: 2.2621571627409915(If you are wondering how the function ended up with the name stdtrit, it is the Student T D
Content Under CC-BY-SA license Is there a t test table in python (numpy, scipy etc)?
WebMar 3, 2018 · Sorted by: 16. You can use the ppf method (i.e. the quantile function) of scipy.stats.t: In [129]: from scipy.stats import t In [130]: alpha = 0.025 In [131]: t.ppf (1 - alpha, df=9) Out [131]: 2.2621571627409915.
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- To find the T critical value in Python, you can use the scipy.stats.t.ppf() function, which uses the following syntax: scipy.stats.t.ppf(q, df) where: 1. q: The significance level to use 2. df: The degrees of freedom The following examples illustrate how to find the T critical value for a left-tailed test, right-tailed test, and a two-tailed test.
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