Understanding Paired T Tests

What is a paired t test primarily used for?

• Analyzing variance

• Comparing two independent samples

• Comparing two paired samples

• Testing for correlation

In a paired t test, what are paired samples also known as?

• Control samples

• Independent samples

• Random samples

• Repeated measures

What is the first step in calculating a paired t test?

• Formulating the null hypothesis

• Collecting data

• Interpreting the p value

• Calculating the t value

What does the null hypothesis in a paired t test state?

• The mean of the differences is zero

• The mean of the differences is greater than zero

• The mean of the differences is less than zero

• The mean of the differences is not zero

How is the t value calculated in a paired t test?

• By adding the mean of the differences to the standard error

• By dividing the mean of the differences by the standard error

• By dividing the mean of the differences by the standard deviation

• By multiplying the mean of the differences by the sample size

What does a p value less than 0.05 indicate?

• The null hypothesis is accepted

• The null hypothesis is rejected

• The alternative hypothesis is rejected

• The test is inconclusive

Which of the following is an assumption of a paired t test?

• The samples are independent

• The samples are normally distributed

• The samples are ordinal

• The samples are categorical

What does a p value of 0.11 suggest about the null hypothesis?

• There is weak evidence against it

• There is strong evidence against it

• It should be accepted

• It should be rejected

What is the main difference between a two-tailed and a one-tailed t test?

• A two-tailed test is used for smaller sample sizes

• A one-tailed test is used for larger sample sizes

• A two-tailed test is more accurate than a one-tailed test

• A two-tailed test checks for any difference, while a one-tailed test checks for a specific direction

When would you use a one-tailed t test?

• When you have a large sample size

• When you have two independent samples

• When you expect a specific direction of change

• When you expect no change