How do you know if an independent samples t-test is significant?
Independent Samples T Tests Hypotheses If the p-value is less than your significance level (e.g., 0.05), you can reject the null hypothesis. The difference between the two means is statistically significant. Your sample provides strong enough evidence to conclude that the two population means are not equal.
What is p-value in independent sample t-test?
In a t test, like in most tests of significance, the significance threshold is traditionally set at p = 0.05. A p-value is basically the likelihood of finding a mean difference by chance if indeed there is no difference in the population.
When should an independent t-test be used?
The Independent Samples t Test is commonly used to test the following: Statistical differences between the means of two groups. Statistical differences between the means of two interventions. Statistical differences between the means of two change scores.
What does ap value less than 0.05 mean?
P > 0.05 is the probability that the null hypothesis is true. 1 minus the P value is the probability that the alternative hypothesis is true. A statistically significant test result (P ≤ 0.05) means that the test hypothesis is false or should be rejected. A P value greater than 0.05 means that no effect was observed.
How do I know if my t-test results are significant?
If you are working with a two-tailed T-Test, double the P-value. Interpret the results. If the result is greater than α, fail to reject the null hypothesis. If you reject the null hypothesis, this implies that your alternative hypothesis is correct, and that the data is significant.
Why do we use independent t-test?
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.
What is a significant p-value?
Article. The p-value can be perceived as an oracle that judges our results. If the p-value is 0.05 or lower, the result is trumpeted as significant, but if it is higher than 0.05, the result is non-significant and tends to be passed over in silence.
What is 0.05 level of significance in testing hypothesis?
The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference.