Alternate Hypothesis: The performance of employees changed after the training program.Null Hypothesis: The employees’ performance did not increase or decrease after training.Let us set the null and alternate hypotheses for this example: We need to perform a paired sample t-test for this data to check if we see a difference before and after the training. After providing a training program, the company re-evaluated the employees’ performance. n = Number of observations of the third data set.Ī company assessed the performance of 10 employees using a scale of 0 to 100.s = Standard deviation of the third data set.The third dataset is the difference between the posttest and pretest data. The formula for calculating the paired sample t-test is: This method is useful when we want to compare data for the same group before and after an experiment or test. In this method, we compare the average of a single group’s data at two different moments. It means there is a big difference between the satisfaction ratings of both restaurants. ![]() Step 3: As per the distribution table, the critical value at a 90% confidence interval with a degree of freedom of 48 will be 1.677. Step 2: Calculate the degree of freedom for a two-sample t-test using the formula Step 1: Let us find the two-sample t-test value using the following formula: Alternate Hypothesis – There is a difference between the average satisfaction rating for the restaurant Easy Eats and Quick Bites. ![]()
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