## What is the difference between a 2 sample independent t-test and an ANOVA?

The t-test is a method that determines whether two populations are statistically different from each other, whereas ANOVA determines whether three or more populations are statistically different from each other.

**What is the difference between independent t-test and ANOVA?**

What are they? The t-test is a method that determines whether two populations are statistically different from each other, whereas ANOVA determines whether three or more populations are statistically different from each other.

**What are independent and repeated measures?**

Independent measures / between-groups: Different participants are used in each condition of the independent variable. Repeated measures /within-groups: The same participants take part in each condition of the independent variable.

### When do we use t-test and chi-square?

Chi-square test is used on contingency tables and more appropriate when the variable you want to test across different groups is categorical. Both t test and ANOVA are used to compare continuous variables across groups. t test is used for only two groups and it compares the means of the two groups.

**Which is the equivalent of the repeated measures ANOVA?**

Repeated measures ANOVA is the equivalent of the one-way ANOVA, but for related, not independent groups, and is the extension of the dependent t-test.

**What is the difference between a t-test and an ANOVA?**

To determine if the mean weight loss between the two groups is significantly different, researchers can conduct an independent samples t-test. 2. Paired samples t-test. This is used when we wish to compare the difference between the means of two groups and where each observation in one group can be paired with one observation in the other group.

#### What’s the difference between an ANOVA and one way ANOVA?

The most commonly used ANOVA tests in practice are the one-way ANOVA and the two-way ANOVA: One-way ANOVA: Used to test whether or not there is a statistically significant difference between the means of three or more groups when the groups can be split on one factor. Example: You randomly split up a class of 90 students into three groups of 30.

**How are Ss subjects treated in repeated measures ANOVA?**

However, with a repeated measures ANOVA, as we are using the same subjects in each group, we can remove the variability due to the individual differences between subjects, referred to as SS subjects, from the within-groups variability (SS w ). How is this achieved? Quite simply, we treat each subject as a block.