In which situations should a researcher use a chi-square test

Davin Sheppard

Davin Sheppard

Answered question

2022-04-21

In which situations should a researcher use a chi-square test instead of a correlation or t-test to conduct a hypothesis test? When should a chi-square goodness of fit test be used relative to a chi-square test for independence?

Answer & Explanation

diehaterzh8s

diehaterzh8s

Beginner2022-04-22Added 11 answers

Answer is explained below
A simple correlation measures the relationship between two variables in which variables have equals status and are not considered independent variables or dependent variables. The chi-square test of independence examines our observed data and tells us whether we have enough evidence to conclude beyond a reasonable doubt that two categorical variables are related.
Stating the hypothesis:
H0: There is no relationship between the two categorical variables (they are independent)
Ha: There is a relationship between the two categorical variables.(They are not independent)
The idea behind the chi-square test, much like ANNOVA, is to determine how far the data are from what is claimed in the null hypothesis.
Chi-square goodness of fit test is a non-parametric test which helps us to find out whether the observed value of a given phenomenon is significantly different from the expected. It is used to compare the observed sample distribution with the expected probability distribution. A chi-square goodness of fit test determines how well theotrical distribution fits the empirical distribution. In this the sample data is divided into intervals and then the numbers of points that fall into the interval are compared, with the expected numbers of points in each interval.
The chi-square test of independence examines our observed data and tells us whether we have enough evidence to conclude beyond a reasonable doubt that the two categorical variables are related.

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