# 3.2 Modeling the Expert: An Introduction to Logistic Regression

## Quick Question

Confusion Matrix #1:

Predicted = 0 Predicted = 1
Actual = 0 15 10
Actual = 1 5 20

Confusion Matrix #2:

Predicted = 0 Predicted = 1
Actual = 0 20 5
Actual = 1 10 15

What is the sensitivity of Confusion Matrix #1?

Exercise 1

Numerical Response

Explanation

The sensitivity of a confusion matrix is the true positives, divided by the true positives plus the false negatives. In this case, it is 20/(20+5) = 0.8

What is the specificity of Confusion Matrix #1?

Exercise 2

Numerical Response

Explanation

The specificity of a confusion matrix is the true negatives, divided by the true negatives plus the false positives. In this case, it is 15/(15+10) = 0.6

## Quick Question

To go from Confusion Matrix #1 to Confusion Matrix #2, did we increase or decrease the threshold value?

Exercise 3

We increased the threshold value.

We decreased the threshold value.

Explanation

We predict the outcome 1 less often in Confusion Matrix #2. This means we must have increased the threshold.