Your firm is interested in learning more about how its salaries relate to its employees' tenure...

^{Your firm is interested in learning more about how its
salaries relate to its employees' tenure with the firm. It has
collected the following data for 25 of its employees.Plot these
data points, and describe using regression how salary relates to
firm tenure for this group. [In response, please provide excel
details]}

Employee Number	Tenure (Years)	Salary ($)
1	15	$53,408
2	32	$77,230
3	14	$53,664
4	20	$55,647
5	25	$60,611
6	14	$51,991
7	28	$71,071
8	30	$69,189
9	28	$67,359
10	17	$50,978
11	14	$56,176
12	6	$38,865
13	21	$58,176
14	11	$52,101
15	14	$50,941
16	32	$73,964
17	29	$67,873
18	33	$73,860
19	27	$60,519
20	16	$48,474
21	26	$69,574
22	3	$34,594
23	14	$52,176
24	9	$56,444
25	14	$57,806

Expert Solution

Tenure is the independent variable and Salary is the dependent variable.

Scatter plot:

Excel Regression output as follows.

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.9277
R Square	0.8606
Adjusted R Square	0.8546
Standard Error	4087.9683
Observations	25

ANOVA
	df	SS	MS	F	Significance F
Regression	1	2373544775	2373544774.9	142.0308	2.53542E-11
Residual	23	384364144.9	16711484.56
Total	24	2757908920

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	36079.0359	2051.8878	17.5833	0.0000	31834.3826	40323.6892
Tenure (Years)	1139.6648	95.6282	11.9177	0.0000	941.8429	1337.4868

Estimated regression equation: Salary ($) = 36,079.0359 + 1,139.6648 x Tenure (years)

It means that as Tenure increases (decreases) by 1 year, Salary increases (decreases) by $1,139.6648.

Since R2 = 0.8606, it means that this model explains 86.06% of variablity of data and is a good fit.

Rahul Sunny answered 7 months ago

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