When To Use Paired T Test

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What is when to use paired t test?

When to use paired t test is a statistical method used to determine if there is a significant difference between the means of two related groups. It is typically used when the data being compared comes from the same subjects or objects, such as before and after measurements, matched pairs, or paired samples.

What are the types of when to use paired t test?

There are two types of paired t tests: dependent and independent. Dependent paired t test is used when the data being compared comes from the same subjects or objects, and the measurements are taken under different conditions (e.g., before and after treatment). Independent paired t test, on the other hand, is used when the data comes from two different but related groups, such as male and female participants or control and experimental groups.

Dependent paired t test
Independent paired t test

How to complete when to use paired t test

To complete a paired t test, follow these steps:

01
Identify the two groups or conditions being compared
02
Collect the data for each group or condition
03
Calculate the mean and standard deviation for each group or condition
04
Perform the paired t test using appropriate statistical software or formula
05
Interpret the results and determine if there is a significant difference between the means

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Questions & answers

A paired t-test is used when we are interested in the difference between two variables for the same subject. Often the two variables are separated by time. For example, in the Dixon and Massey data set we have cholesterol levels in 1952 and cholesterol levels in 1962 for each subject.
When two datasets are of equal length and each observation in one dataset can be “paired” with an observation in another dataset, we call this paired data. In order for two datasets to be paired, it's important that each observation in one dataset can only be paired with one observation in the other dataset.
When two datasets are of equal length and each observation in one dataset can be “paired” with an observation in another dataset, we call this paired data. In order for two datasets to be paired, it's important that each observation in one dataset can only be paired with one observation in the other dataset.
As we saw above, a 1-sample t-test compares one sample mean to a null hypothesis value. A paired t-test simply calculates the difference between paired observations (e.g., before and after) and then performs a 1-sample t-test on the differences.
The “driving after having 2 beers” example is a case in which observations are paired by subject. In other words, both samples have the same subject, so that each subject is measured twice.
How to Perform a Paired t-Test by Hand Step 1: Calculate the Test Statistic. Step 2: Calculate the Critical Value. Step 3: Reject or Fail to Reject the Null Hypothesis.
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