How do you know when to use a paired or unpaired t-test?

A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal. In a paired t-test, the variance is not assumed to be equal.

What are the conditions for a paired t-test?

The paired sample t-test has four main assumptions:

• The dependent variable must be continuous (interval/ratio).
• The observations are independent of one another.
• The dependent variable should be approximately normally distributed.
• The dependent variable should not contain any outliers.

Why do we use matched pairs t-test?

A matched-pairs t-test is used to test whether there is a significant mean difference between two sets of paired data.

Is a paired t-test dependent or independent?

The purpose of the test is to determine whether there is statistical evidence that the mean difference between paired observations is significantly different from zero. The Paired Samples t Test is a parametric test. This test is also known as: Dependent t Test.

How do you do a paired t-test?

Paired Samples T Test By hand

1. Example question: Calculate a paired t test by hand for the following data:
2. Step 1: Subtract each Y score from each X score.
3. Step 2: Add up all of the values from Step 1.
4. Step 3: Square the differences from Step 1.
5. Step 4: Add up all of the squared differences from Step 3.

What is a paired sample t-test and when is it used?

A paired t-test is used to compare two population means where you have two samples in which observations in one sample can be paired with observations in the other sample.

What does a paired sample t-test tell you?

The Paired Samples t Test compares the means of two measurements taken from the same individual, object, or related units. These “paired” measurements can represent things like: A measurement taken at two different times (e.g., pre-test and post-test score with an intervention administered between the two time points)

When should you use an independent samples t test?

You should use this test when: You do not know the population mean or standard deviation. You have two independent, separate samples.

What is the difference between paired and independent t tests?

Paired-samples t tests compare scores on two different variables but for the same group of cases; independent-samples t tests compare scores on the same variable but for two different groups of cases.

What is a paired sample test?

What are the assumptions of a paired t test?

The paired sample t-test has four main assumptions: • The dependent variable must be continuous (interval/ratio). • The observations are independent of one another. • The dependent variable should be approximately normally distributed. • The dependent variable should not contain any outliers.

When to use the Z-test versus t-test?

Statistical Tests – When to use Which? Relationship between p-value, critical value and test statistic. As we know critical value is a point beyond which we reject the null hypothesis. Z-test. In a z-test, the sample is assumed to be normally distributed. T-test. A t-test is used to compare the mean of two given samples. ANOVA. Chi-Square Test. Reference

When to use an one sample t test?

The one-sample t-test is used to determine whether a sample comes from a population with a specific mean. This population mean is not always known, but is sometimes hypothesized.

When is Z test appropriate over the t test?

Z-test is used to when the sample size is large, i.e. n > 30, and t-test is appropriate when the size of the sample is small , in the sense that n < 30.