Explain how the chisquare tests differ from parametric tests

Explain how the chi-square tests differ from parametric tests (such as t-tests or ANOVA) with regard to:

A. the hypotheses

B. the data that is collected

C. the assumptions underlying the test

Solution

Explain how the chi-square tests differ from parametric tests (such as t-tests or ANOVA) with regard to:

the hypotheses

In parametric tests, the hypotheses are about parameters. Like whether the population means are equal or populations variances are equal. But in chi square test hypothesis, we are not mentioning any parameters. We simply stat whether any relation exists between two variables or not.

the data that is collected

The level of measurement is ordinal or nominal data for chi square test.

For parametric test we need the level of measurement is at least in interval scale.

the assumptions underlying the test

Parametric statistics test hypotheses based on the assumption that the samples come from populations that are normally distributed where as Nonparametric statistical procedures test hypotheses that do not require normal distribution or variance assumptions about the populations from which the samples were drawn.