A researcher conducts a t test for dependent means in which it is predicted that there will be a decrease in unemployment from before to after a particular job-skills training program. The cutoff "t" needed is -1.8333. The standard deviation of the distribution of means of change scores is 2.0 and the mean change score for the sample studied is an increase of 5.2.
What is the t score?
2.60
To calculate the t score, we need to use the formula:
t = (mean change score - hypothesized mean change score) / (standard deviation of the distribution of means of change scores / square root of the sample size)
In this case, the mean change score for the sample studied is an increase of 5.2, which means the hypothesized mean change score would be 0 (since it is predicted that there will be a decrease in unemployment). The standard deviation of the distribution of means of change scores is 2.0.
Let's calculate the t score:
t = (5.2 - 0) / (2.0 / √n)
Since the sample size (n) is not given, we cannot calculate the precise t score. The t score is dependent on the sample size. However, we do know the desired cutoff t value is -1.8333. This cutoff value represents the critical value or critical t-score.
So, unfortunately, without the sample size, we cannot determine the exact t score in this case.