How to find Z critical value in Python?

In this article, we are going to learn about how to find the Z Critical Value in Python.

What is the Z critical value?

In statistics, the area under the commonly used normal model is called the Z critical value. Shows the probability for each possible variable. When we perform a hypothesis test, what is produced is a test statistic. To determine whether the results of a hypothesis test are statistically significant, you can compare the test statistic to the Z critical value. A result is considered statistically significant when its absolute value exceeds the Z critical value. This tutorial will show you how to determine the Z critical value in Python.

When performing a hypothesis test, you will get a test statistic as the result. In order to determine whether the results of a hypothesis test are statistically significant, the test statistic needs to be compared with the Z critical value. If the absolute value of the test statistic exceeds the Z critical value, the test result is statistically significant.

grammar

In Python, you can use the scipy.stats.norm.ppf() method to get the Z critical value, the syntax is as follows −

scipy.stats.norm.ppf(q)

where q represents the significance level to be used.

Z critical value in Python

1. Left tail test

Suppose we want to determine the Z critical value of a left-tailed test with a significance level of 0.05 −

Example

!pip3 install scipy import scipy.stats #find Z critical value scipy.stats.norm.ppf(.05)

Output

-1.6448536269514729

The value of key value Z is -1.64485. If the test statistic is below this threshold, the test result is statistically significant.

2. Right tail test

Suppose we are looking for a Z critical value for a right-tailed test with a significance level of 0.05 −

Example

import scipy.stats #find Z critical value scipy.stats.norm.ppf(1-.05)

Output

1.6448536269514722

Z is 1.64485. Therefore, if the test statistic is higher than this number, the test result is considered statistically significant.

3. Two-tailed test

Suppose we are looking for the Z critical value for a two-tailed test with a significance level of 0.05 -

Example

import scipy.stats #find Z critical value scipy.stats.norm.ppf(1-.05/2)

Output

1.959963984540054

There are always two essential values when you do a two-tailed test. 1.95996 and -1.95996 are the Z critical values in this situation. Therefore, the test's findings are statistically significant if the test statistic is either less than -1.95996 or more than 1.95996.

in conclusion

In statistics, the Z-critical value is used to determine insights from the data so machine learning models can use it and make predictions based on it.

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