1. Test of independence:

A sample of several observations is collected from a population, the researcher wants to determine whether two or more attributes are independent of each other, or associated with each other. Each observation is present at one of the levels of the attributes considered.

Step 2

2. Chi-square goodness of fit:

Chi-square goodness of fit test is a non-parametric test used to find how the observed value of a given phenomena is significantly different from the expected value. In Chi-square goodness of fit test the term goodness of fit is used to compare the observed sample distribution with the expected probability distribution.

The null hypothesis assumes that there is no significant difference between the observed and expected value and the alternative assumes that there is a significant difference between the observed and expected value.

Assumption of goodness of fit test:

-The data is obtained from a simple random sampling.

-The variable under study is categorical.

-The each cell count (for each category) is at least 5 and the observations are independent.

3. The categorical variable are used for a chi-square tests.

A sample of several observations is collected from a population, the researcher wants to determine whether two or more attributes are independent of each other, or associated with each other. Each observation is present at one of the levels of the attributes considered.

Step 2

2. Chi-square goodness of fit:

Chi-square goodness of fit test is a non-parametric test used to find how the observed value of a given phenomena is significantly different from the expected value. In Chi-square goodness of fit test the term goodness of fit is used to compare the observed sample distribution with the expected probability distribution.

The null hypothesis assumes that there is no significant difference between the observed and expected value and the alternative assumes that there is a significant difference between the observed and expected value.

Assumption of goodness of fit test:

-The data is obtained from a simple random sampling.

-The variable under study is categorical.

-The each cell count (for each category) is at least 5 and the observations are independent.

3. The categorical variable are used for a chi-square tests.