![]() Looking this up in a t-table (or calculating it in your favorite stats program) you find a p-value < 0.001. The degrees of freedom is 38 (n–1 for each group). This means that the difference in group means is 12.79 standard deviations away from the mean of the distribution of the null hypothesis. ![]() Example of a p-valueThe two-tailed t-test of the difference in test scores generates a t-value of 12.79. The t-score which generates a p-value below your threshold for statistical significance is known as the critical value of t, or t*. While most statistical programs will automatically calculate the corresponding p-value for the t-score, you can also look up the values in a t-table, using your degrees of freedom and t-score to find the p-value. The test statistic for t-tests and regression tests is the t-score. They then calculate a p-value that describes the likelihood of your data occurring if the null hypothesis were true. Statistical tests generate a test statistic showing how far from the null hypothesis of the statistical test your data is. From the t-test you find the difference in average score between class 1 and class 2 is 4.61, with a 95% confidence interval of 5.31 to 3.88.īecause the confidence interval does not cross zero, and is in fact quite far from zero, it is unlikely that this difference in test scores could have occurred under the null hypothesis of no difference between groups. Using a two-tailed t-test, you generate an estimate of the difference between the two classes and a confidence interval around that estimate. Example of a confidence intervalYou have sampled 20 students from two different classes to estimate the mean standardized test scores and want to know if there is a difference between the two groups. The t-score used to generate the upper and lower bounds is also known as the critical value of t, or t*.
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