Example. An instructor is interested in the correlation between the number of absences and a student's final grade. She collects data for her classes and selects a random sample of 20 students from two different terms. Then she finds the least squares line using x = number of days absent as the predictor variable and y = final score as the response variable. The equation of the line is found to be 4 =- 2.3558692z + 92.614042. Identify and interpret the slope in context. Answer. The slope of the line is -2.3558692. This means for each additional day missed by a student, we expect the final score to be reduced by about 2.4 points. Practice After their classes were completed, the least squares line was computed for a random sample of 25 students who took Math 54. The predictor variable used was the homework point score and the response variable was the final point score in the class. The equation of the least squares line was 4 = 0.635029982 + 20.956632. Using complete sentences, identify the slope of the line and interpret its meaning in context