NHST table

As seen in the video, Null Hypothesis Significance Testing (NHST) is a statistical method used to test whether or not you are able to reject or retain the null hypothesis. This type of test can confront you with a type I error. This happens when the test rejects the null hypothesis, while it is actually true in reality. Furthermore, the test can also deliver a type II error. This is the failure to reject a null hypothesis when it is false. All hypothesis tests have a probability of making type I and II errors.

Sensitivity and specificity are two concepts that statisticians use to measure the performance of a statistical test. The sensitivity of a test is its true positive rate:

\(\mathrm{sensitivity} = \frac{\mathrm{number\ of\ true\ positives}}{\mathrm{number\ of\ true\ positives} + \mathrm{number\ of\ false\ negatives}}\)

The specificity of a test is its true negative rate:

\(\mathrm{specificity} = \frac{\mathrm{number\ of\ true\ negatives}}{\mathrm{number\ of\ true\ negatives} + \mathrm{number\ of\ false\ positives}}\)

Calculate both the sensitivity and specificity of the test based on numbers displayed in the NHST table?