The first dataset contains cross-sectional data, that is, datacollected at approximately the same point in time. This data iscontained in the Excel file MircoAnalysis.Here you have to analyze the given data to understand what impact 6potential variables have on salary. Regression in thisexample is used to explain the impact of possible variables.

You will have to examine the data and make necessarymodifications to create a multiple regression model.

In addition to the model output (from Excel), answer thefollowing on the tab “Final Regression Model”:

How does each independent variable in your model, affectthe salary?

What is the r-squared value and what does it mean tosalary?

Which variables (even if they may not end up being inthe final model) required transformation into dummyvariables?

Data Set:

Salary	Years_Previous_Experience	Years_Employed	College degree	Gender	Department	Number_Supervised
$31,223	0	0	None	Male	Advertising	2
$49,563	9	19	BS	Female	Advertising	6
$48,196	6	6	BS	Male	Engineering	2
$72,467	5	12	MBA	Male	Engineering	0
$46,027	5	7	BS	Male	Engineering	1
$52,461	6	9	BS	Male	Engineering	1
$70,269	0	25	MBA	Female	Advertising	3
$102,033	3	22	PHD	Female	Engineering	45
$41,617	11	3	None	Female	Sales	6
$108,983	0	27	PHD	Male	Engineering	44
$54,457	4	9	MBA	Female	Engineering	4
$51,460	7	18	MBA	Female	Sales	5
$60,999	5	14	MBA	Male	Engineering	5
$41,481	6	7	BS	Male	Advertising	6
$52,573	6	18	BS	Male	Sales	5
$46,843	2	8	None	Male	Engineering	2
$47,033	4	6	BS	Female	Engineering	2
$39,436	0	2	None	Male	Purchasing	5
$34,917	3	1	None	Male	Engineering	0
$76,835	19	6	MBA	Female	Engineering	40
$46,816	6	3	MBA	Male	Purchasing	3
$72,176	3	20	MBA	Male	Advertising	4
$32,669	2	6	None	Male	Sales	1
$74,350	3	12	MBA	Female	Purchasing	6
$57,650	9	6	BS	Female	Purchasing	2
$46,818	5	9	BS	Male	Purchasing	5
$45,185	2	6	MBA	Female	Engineering	3
$43,272	1	0	MBA	Female	Purchasing	0
$35,043	1	5	None	Female	Engineering	2
$55,293	16	22	MBA	Female	Sales	7
$48,274	1	6	BS	Female	Purchasing	2
$51,204	4	21	BS	Female	Sales	9
$35,083	6	0	None	Male	Purchasing	2
$43,454	3	15	MBA	Male	Sales	4
$48,163	5	6	None	Female	Engineering	3
$62,748	5	15	MBA	Female	Advertising	4
$48,283	4	4	MBA	Female	Advertising	8
$51,917	3	9	MBA	Male	Engineering	1
$90,321	2	25	PHD	Female	Engineering	1
$68,241	6	18	MBA	Female	Engineering	1
$60,963	3	20	BS	Female	Engineering	1
$48,089	4	9	BS	Male	Purchasing	2
$45,714	4	5	BS	Female	Engineering	0
$39,003	6	5	None	Female	Sales	0
$46,183	6	9	None	Male	Engineering	3
$38,260	1	0	BS	Male	Sales	4