What are the assumptions behind the sample t-test?

The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size, and equality of variance in standard deviation.

What are the assumptions of a two sample t-test?

Two-sample t-test assumptions Data in each group must be obtained via a random sample from the population. Data in each group are normally distributed. Data values are continuous. The variances for the two independent groups are equal.

How do you test assumptions for t-test?

Assumptions

1. Independence of the observations. Each subject should belong to only one group.
2. No significant outliers in the two groups.
3. Normality. the data for each group should be approximately normally distributed.
4. Homogeneity of variances. the variance of the outcome variable should be equal in each group.

Which t-test is within subjects?

A dependent t-test is an example of a “within-subjects” or “repeated-measures” statistical test. This indicates that the same participants are tested more than once. Thus, in the dependent t-test, “related groups” indicates that the same participants are present in both groups.

What are the assumptions of a within-subjects t test?

Within-subjects t-test assumptions. the dependent variable is continuous (interval or ratio). Outcome scores are related to/correlated with/dependent on each other in some way. This is really the defining feature of a between or within-subject t-test.

What are the pros and cons of between subjects design?

1 Using a between-subjects design. In a between-subjects design, there is usually at least one control group and one experimental group, or multiple groups that differ on a variable (e.g., gender, 2 Between-subjects versus within-subjects design. 3 Pros and cons of a between-subjects design.

When to use within-subjects t-test in paired data?

If you’re dealing with paired data, you would want to look at a within-subjects t-test instead. the dependent variable is continuous (interval or ratio). Outcome scores are related to/correlated with/dependent on each other in some way.

What do you call a between subjects design?

A between-subjects design is also called an independent measures or independent-groups design because researchers compare unrelated measurements taken from separate groups.