What is The Difference between Student T-Test And Chi-Square Test?

Aamir Kamal 🚀
1 min readDec 30, 2019

In Probability distribution, we study the Chi-square test as well as Student T-test.

Photo by Raghav Modi on Unsplash

Chi-square test helps you to find the type of relationship between Variables where the null hypothesis and alternative hypothesis are involved. If you reject the null hypothesis then that means that there is a relationship that exists between the Null hypothesis and alternative hypothesis. The null hypothesis is the baseline of any experiment while the alternative hypothesis is presented to counter the claim.

In the student T-test, we have a sample variance and a population variance which is equal to zero.

Different between T-Test and Chi-square Test

  1. T-test allows you to differentiate between the two groups. While the Chi-square test also helps you to find the relationship between two variables but has no direction and size of the relationship.
  2. Null hypothesis: In the T-test, there is no stat. difference between the two groups while in the Chi-square test there is no relationship between two variables.

I hope this will helps you.

Aamir Kamal 🚀

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