Question

#11.     Consider the (fictitious) data labelled “problem # 11” which gives starting salaries of fresh graduates and their CGPA at the time of graduation.

(i) Construct a simple linear regression model that predicts the starting salary of a fresh graduate based on his/her CGPA. (a) clearly write the model, and (b) quote the R2 from Excel output and interpret the number. (10 + 5 =15 points)









(ii) Using your model in (i) estimate the starting salary of a fresh graduate who has CGPA of 3.25, and interpret your answer (10 points)

GPA	Salary ($)
2.65	48898
3.53	66553
2.5	47650
3.99	74210
2.94	53460
4	73708
3.06	57454
3.78	69262
3.79	69818
3.82	70390
3.54	66645
2.79	54046
3.27	61225
2.96	56470
3.1	58210
2.91	55857
3.74	70906
2.57	48433
3.54	65096
3.19	59231
3.72	69135
3.83	72835
3.32	61292
3.79	70182
3.35	64225

Answer 1

Sol:

Install analysis toolpak in excel

Go to

Data >Data analysis>Regression

select Y as Salary

X as GPA

Click ok

We get

From output:

t a simple linear regression model that predicts the starting salary of a fresh graduate based on his/her CGPA

Salary=2783.052507+17873.02447*GPA

slope=17873.02447

Y intercept=2783.052507

Rsq=0.987321651

98.73% variation in Salary is explained by GPA

Good model

(ii) Using your model in (i) estimate the starting salary of a fresh graduate who has CGPA of 3.25, and interpret your answer (10 points)

we have

Salary=2783.052507+17873.02447*GPA

For GPA=3.25

Predicted salary=2783.052507+17873.02447*3.25

=60870.38

Predicted salary is 60870.38