How do I Find a P-Value from a t-Score in Python?

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Often in statistics we’re interested in determining the associated with a certain t-score that results from a . If this p-value is below some significance level, we can reject the null hypothesis of our hypothesis test.

To find the p-value associated with a t-score in Python, we can use the , which uses the following syntax:

scipy.stats.t.sf(abs(x), df)

where:

• x: The t-score
• df: The degrees of freedom

The following examples illustrate how to find the p-value associated with a t-score for a left-tailed test, right-tailed test, and a two-tailed test.

Left-tailed test

Suppose we want to find the p-value associated with a t-score of -0.77 and df = 15 in a left-tailed hypothesis test.

import scipy.stats

#find p-value
scipy.stats.t.sf(abs(-.77), df=15)

0.2266283049085413

The p-value is 0.2266. If we use a significance level of α = 0.05, we would fail to reject the null hypothesis of our hypothesis test because this p-value is not less than 0.05.

Right-tailed test

Suppose we want to find the p-value associated with a t-score of 1.87 and df = 24 in a right-tailed hypothesis test.

import scipy.stats

#find p-value
scipy.stats.t.sf(abs(1.87), df=24)

0.036865328383323424

The p-value is 0.0368. If we use a significance level of α = 0.05, we would reject the null hypothesis of our hypothesis test because this p-value is less than 0.05.

Two-tailed test

Suppose we want to find the p-value associated with a t-score of 1.24 and df = 22 in a two-tailed hypothesis test.

import scipy.stats

#find p-value for two-tailed test
scipy.stats.t.sf(abs(1.24), df=22)*2

0.22803901531680093

The p-value is 0.2280. If we use a significance level of α = 0.05, we would fail to reject the null hypothesis of our hypothesis test because this p-value is not less than 0.05.

Related: You can also use this online to find p-values.