When do we use t test?When n is greater than or equal to 30when nominal data is givenWhen ordinal data is givenWhen n < 30

We use a t-test in statistics to compare the means of two groups and determine if there is a significant difference between them. This test is most appropriate when:

1. The sample size (n) is less than 30. If n is greater than or equal to 30, a z-test might be more appropriate due to the Central Limit Theorem.

2. The data is interval or ratio scale (continuous). T-tests are not appropriate for nominal (categorical) data. For nominal data, chi-square tests are often used.

3. The data can also be ordinal as long as it can be assumed that the intervals between the scale values are equal. However, non-parametric tests are often used for ordinal data as they do not require this assumption.

4. The data follows a normal distribution. If the data does not follow a normal distribution, non-parametric tests like the Mann-Whitney U test might be more appropriate.

5. The variances of the two groups being compared are equal. If the variances are not equal, a different version of the t-test called Welch's t-test can be used.