- Why is a paired t test more powerful?
- When can we reject the null hypothesis?
- Why do we reject the null hypothesis?
- How do you accept or reject the null hypothesis in regression?
- How do you know if variance is equal or unequal?
- How do you know if data is paired or unpaired?
- What is the null hypothesis for a paired t test?
- What is the null hypothesis for an independent t test?
- What do paired t tests show?
- What is the difference between a T test and an Anova?
- What is an independent t test used for?
- What does a 2 sample t test tell you?
- How do you reject the null hypothesis in t test?

## Why is a paired t test more powerful?

Paired t-tests are considered more powerful than unpaired t-tests because using the same participants or item eliminates variation between the samples that could be caused by anything other than what’s being tested..

## When can we reject the null hypothesis?

The convention in most biological research is to use a significance level of 0.05. This means that if the P value is less than 0.05, you reject the null hypothesis; if P is greater than or equal to 0.05, you don’t reject the null hypothesis.

## Why do we reject the null hypothesis?

If the P-value is less than (or equal to) , then the null hypothesis is rejected in favor of the alternative hypothesis. And, if the P-value is greater than , then the null hypothesis is not rejected. … Using the sample data and assuming the null hypothesis is true, calculate the value of the test statistic.

## How do you accept or reject the null hypothesis in regression?

The p-value for each term tests the null hypothesis that the coefficient is equal to zero (no effect). A low p-value (< 0.05) indicates that you can reject the null hypothesis.

## How do you know if variance is equal or unequal?

An F-test (Snedecor and Cochran, 1983) is used to test if the variances of two populations are equal. This test can be a two-tailed test or a one-tailed test. The two-tailed version tests against the alternative that the variances are not equal.

## How do you know if data is paired or unpaired?

Paired means that both samples consist of the same test subjects. A paired t-test is equivalent to a one-sample t-test. Unpaired means that both samples consist of distinct test subjects. An unpaired t-test is equivalent to a two-sample t-test.

## What is the null hypothesis for a paired t test?

The null hypothesis is that the mean difference between paired observations is zero. When the mean difference is zero, the means of the two groups must also be equal. Because of the paired design of the data, the null hypothesis of a paired t–test is usually expressed in terms of the mean difference.

## What is the null hypothesis for an independent t test?

The null hypothesis for an independent samples t-test is that two populations have equal means on some metric variable. For example, do men spend the same amount of money on clothing as women? We can’t reasonably ask the entire population of men and women how much they spend.

## What do paired t tests show?

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. … Since we are ultimately concerned with the difference between two measures in one sample, the paired t-test reduces to the one sample t-test.

## What is the difference between a 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 an independent t test used for?

The Independent Samples t Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. The Independent Samples t Test is a parametric test.

## What does a 2 sample t test tell you?

The two-sample t-test (also known as the independent samples t-test) is a method used to test whether the unknown population means of two groups are equal or not.

## How do you reject the null hypothesis in t test?

If the absolute value of the t-value is greater than the critical value, you reject the null hypothesis. If the absolute value of the t-value is less than the critical value, you fail to reject the null hypothesis.