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?

Possible answers

The sensitivity is 0.85 and the specificity is 0.89.

The sensitivity is 0.94 and the specificity is 0.82.

The sensitivity is 0.89 and the specificity is 0.85.

The sensitivity is 0.82 and the specificity is 0.94.

Exercise

NHST table

Instructions

Possible answers