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How to Find the 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 Z Critical Value?
In statistics, the region under the common normal model is referred to as the Z critical value. Every possible variable's probability is shown. A test statistic is what is produced when we do a hypothesis test. To determine if the outcome of the hypothesis test is statistically significant, the test statistic can be compared to a Z critical value. An outcome is regarded as statistically significant when its absolute value exceeds the Z critical value. The determination of Z critical value in Python will be covered in this tutorial.
When you do a hypothesis test, you will receive a test statistic as a consequence. To see if the hypothesis test findings are statistically significant, compare the test statistic to a Z critical value. If the absolute value of the test statistic exceeds the Z critical value, the test findings are statistically significant.
Syntax
In Python, you may get the Z critical value using the scipy.stats.norm.ppf() method, which has the following syntax −
scipy.stats.norm.ppf(q)
where q represents, the significance level to use.
Z critical value in python
1. Left-tailed test
Let's say we wish to determine the Z critical value for a left-tailed test with a.05 levels of significance −
Example
!pip3 install scipy import scipy.stats #find Z critical value scipy.stats.norm.ppf(.05)
Output
-1.6448536269514729
The crucial value for Z is -1.64485. The test's results are thus statistically significant if the test statistic is below this threshold.
2. Right-tailed test
Let's say we're looking for the Z critical value for a right-tailed test with a.05 levels of significance −
Example
import scipy.stats #find Z critical value scipy.stats.norm.ppf(1-.05)
Output
1.6448536269514722
The crucial number for Z is 1.64485. The test's results are thus considered statistically significant if the test statistic is higher than this number.
3. Two-tailed test
Let's say we're looking for the Z critical value for a two-tailed test with a.05 levels of significance −
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.
Conclusion
In statistics, Z critical value is used to determine the insights of the data, so the machine learning model can use it and gives prediction based on it.
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