How to calculate dependent samples t-test based on correlation?
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Methods Manual: t-test - hand calculation - for paired samples*
List the raw scores by groupSubtract each Y score from each X score (d).Square each d and sum.
4. Use the following formula to calculate the t-ratio.

d = difference between matched scores
N = number of pairs of scores
5. Find the probability value (p) associated with the obtained t-ratio.
6. Calculate degrees of freedom (df)
df = N (number of pairs) - 1
df = 11-1 = 10
7. Use the abbreviated table of Critical Values for t-test to find the p value.
For this example, t = -2.35, df = 10. The obtained value of 2.35 exceeds the cutoff of 2.11 (df = 17, nearest df shown on the table) at the .05 level. Therefore, p <.05. In a report the result is shown as t(17) = -2.35, p<.05.
A plus or minus sign at the end, associated with the t-ratio, indicates the direction of the difference between the means (anxiety was higher on exam day). The p value remains the same in either direction.
* If you have independent samples (i.e., two different groups of subjects), you must use a different formula. See t-test for independent samples.
List the raw scores by groupSubtract each Y score from each X score (d).Square each d and sum.
4. Use the following formula to calculate the t-ratio.

d = difference between matched scores
N = number of pairs of scores
5. Find the probability value (p) associated with the obtained t-ratio.
6. Calculate degrees of freedom (df)
df = N (number of pairs) - 1
df = 11-1 = 10
7. Use the abbreviated table of Critical Values for t-test to find the p value.
For this example, t = -2.35, df = 10. The obtained value of 2.35 exceeds the cutoff of 2.11 (df = 17, nearest df shown on the table) at the .05 level. Therefore, p <.05. In a report the result is shown as t(17) = -2.35, p<.05.
A plus or minus sign at the end, associated with the t-ratio, indicates the direction of the difference between the means (anxiety was higher on exam day). The p value remains the same in either direction.
* If you have independent samples (i.e., two different groups of subjects), you must use a different formula. See t-test for independent samples.
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