Question

QUESTION 3

1. A national job placement company is interested in developing a model that might be used to explain the variation in starting salaries for college graduates based on the college GPA score. The following data were collected through a random sample of the clients with which this company has been associated.

GPA Score	Starting Salary (RM)
3.20	3,500
3.40	2,950
2.90	3,000
3.60	3,640
2.80	3,150
2.50	2,900
3.00	3,320
3.60	3,760
2.90	3,200
3.50	3,600

Based on this sample information,

1. Sketch a scatter plots to illustrate the relationship between GPA Score and starting salary. Give a brief description of the sketched diagram that has been produced.

2. Obtain the relationship between score GPA and starting salary model by using the least squares regression method.

3. Determine what percent of the variation in starting salaries is explained by GPA score.

4. Draw the regression line on the scatter plot in part (i).

Answer 1

Answer i)

Scatter plot is as depicted below:

From the scatter plot. it can be seen that there is positive association between GPA Score and starting salary. In other words, as the GPA score increases, starting salary also increase.

Answer ii)

The regression equation can be written as:

Starting Salary = 1352.461 + 620.872xGPA Score

Answer iii)

Correlation coefficient is calculated as follows:

Coefficient of Determination = r² = 0.7575*0.7575

Coefficient of Determination = 0.5738

Since coefficient of determination is 0.5738, it can be said that 57.38% of the variation in starting salaries is explained by GPA score.

Answer iv)

Following is the scatter chart showing regression line: