Question

use the situation below to answer questions 15 and 16: college admissions use past data to predict how successful (measured as college gpa) a student will be based on their high school success (measured as high school gpa). 15) which of the following is the best description of the scatter - plot? (a) there is a strong, positive, linear relationship between high school gpa and college gpa. (b) there is a weak, positive, scattered relationship between high school gpa and college gpa. (c) there is a strong scattered relationship between high school gpa and college gpa. (d) there is a positive, linear relationship with a single outlier between high school gpa and college gpa. (e) there is a moderate, negative, linear relationship between high school gpa and college gpa. 16) there is an influential point at the ordered pair (1.5, 2.1). if you were to remove this point from the data, what would happen to the slope and the y - intercept? (a) the slope and the y - intercept will both increase. (b) the slope and the y - intercept will both decrease. (c) the slope will increase and the y - intercept will decrease. (d) the slope will decrease and the y - intercept will increase. (e) we cannot know the answer without knowing the original regression equation.

Explanation:

Step1: Analyze scatter - plot for question 15

The points in the scatter - plot are not tightly clustered around a line, so it's not a strong relationship. As high school GPA increases, college GPA generally increases, so it's a positive relationship.

Step2: Analyze effect of removing a point for question 16

The point (1.5, 2.1) is below the general trend of the other points. Removing it will pull the regression line up, increasing both the slope and the y - intercept.

Answer:

1. B. There is a weak, positive, scattered relationship between High School GPA and College GPA.
2. A. The slope and the y - intercept will both increase.