## What does it mean to reject the null hypothesis in at test?

When your p-value is less than or equal to your significance level, you reject the null hypothesis. Your results are statistically significant. When your p-value is greater than your significance level, you fail to reject the null hypothesis. Your results are not significant.

### What rejects the null hypothesis?

Rejecting or failing to reject the null hypothesis If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis.

#### How do you know if t-value is significant?

So if your sample size is big enough you can say that a t value is significant if the absolute t value is higher or equal to 1.96, meaning |t|≥1.96.

**How do you accept or reject the null hypothesis?**

Set the significance level, , the probability of making a Type I error to be small — 0.01, 0.05, or 0.10. Compare the P-value to . If the P-value is less than (or equal to) , reject the null hypothesis in favor of the alternative hypothesis. If the P-value is greater than , do not reject the null hypothesis.

**How do you use the p-value to reject the null hypothesis?**

If the p-value is less than 0.05, we reject the null hypothesis that there’s no difference between the means and conclude that a significant difference does exist. If the p-value is larger than 0.05, we cannot conclude that a significant difference exists.

## What is the purpose of t-test in research?

A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics.

### What does a negative T value mean?

A negative t-value indicates a reversal in the directionality of the effect, which has no bearing on the significance of the difference between groups.

#### Why do we reject the null hypothesis when the p-value is small?

The p-value is used as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected. A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.

**How to determine whether to reject the null hypothesis using t-value?**

Using the t-value to determine whether to reject the null hypothesis. To determine whether to reject the null hypothesis using the t-value, compare the t-value to the critical value. The critical value is t α/2, n–p-1, where α is the significance level, n is the number of observations in your sample, and p is the number of predictors.

**How do you find the critical value of a null hypothesis?**

Using the t-value to determine whether to 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. You can calculate the critical value in Minitab or find the critical value from a t-distribution table in most statistics books.

## What happens if we can’t reject the null hypothesis in SPSS?

So when we run our t-test (using SPSS), if we obtain a value that is greater than 2.042, we can reject the Null hypothesis. Q: What happens if we can’t reject the Null? A: Too bad 🙂 It could indicate that the difference you observe between the means of the 2 groups are due to chance or sampling error, etc.

### What happens if the t-value is greater than the critical value?

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. You can calculate the critical value in Minitab or find the critical value from a t-distribution table in most statistics books.