I dont understand 26 and 27

Let X = quiz 1 score and Y = quiz 2 score. Suppose 5 students have the following scores, given as quiz 1 score, quiz 2 score (or as X, Y]: Student 1: 10, 10 Student 2: 9. 8 Student 3: Student 4: 5,9 Student 5: The regression analysis shows R-squared = $8%. The results are below. (Assume the scatterplot shows a linear relationship.) Coefficient Standard Lower Upper Error t Stat Pvalue 95%% 95N Intercept 4.012987 1985322 2021328 0.136481 2.30519 10.33117 Quir 1 0.525974 0.260686 2017657 0.136966 0.30364 1.355592 From the above information and the data set: 25. Draw the scatterplot STAT 1430 Recitation 4B Regression Quiz One Vs Quiz Two Que Two 10 11 Quiz One 26. Write down the equation for the best-fitting line. 7.65 +0.151*Quiz 1 27. Find each of the 5 residuals for this data set. (Remember what a residual and how it is calculated from your lecture notes.) [This is more challenging try to answer without your TA's help - use those around you AND your lecture notes!] First, you will take a quiz 1 score and its matching quiz two score in the data. Then, take the same quiz one score and input it into the regression line. This will produce the predicted quiz two score, Then take the observed number (Y) and the predicted number (Y) and you will find the residual. Doing this for each data set, the residuals are .84, -1.01,-.56,.6, and .14