Chi-Square Test vs. F Test
What is the difference between Chi-square test and F Test?
These two statistical procedures are used for different purposes.
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The chi-square test is used when you want to know whether there is a statistical difference between two categorical variables (e.g., gender and preferred car color).
The F test, on the other hand, is used when you want to know whether there is a statistical difference between two continuous variables (e.g., height and weight).
The chi-square test is non parametric. That means this test does not make any assumption about the distribution of the data.
The F test is a parametric test. It assumes that data are normally distributed and that samples are independent from one another.
Types of Tests:
Chi square test:
- For testing the population variance against a specified value
- For testing goodness of fit of some probability distribution
- Testing for independence of two attributes (Contingency Tables)
- For testing equality of two variances from different populations
- For testing equality of several means with technique of ANOVA.