It looks like you've uploaded a photo of a math review sheet related to linear regression. The problem involves finding the linear regression equation and making predictions based on a dataset that includes the number of classes missed and final exam scores.

Let me first summarize the steps for this problem:

1. Linear Regression Equation: The goal is to write the linear regression equation for the data set, which requires performing a regression analysis to determine the slope and y-intercept.

2. Correlation Coefficient: You need to find the correlation coefficient, which shows how strongly the two variables are related.

3. Prediction for 12 missed classes: Based on the regression equation, you are asked to predict a final exam score for a student who missed twelve classes.

4. Prediction for a final exam score of 93: You are also tasked with predicting how many classes a student missed when their final exam score is 93.

From the handwriting on the page, the regression analysis has already been partially performed, and some results like "m" (slope) and "b" (y-intercept) appear to have been calculated. I can help walk through the exact interpretation and further calculations based on this data.

Would you like me to go over the entire process or focus on a particular part? Let me know how you’d like to proceed.