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.