Question

Individual	Bettendorf Salary	Experience (X1)	Education (X2)	Sex (X3)
1	53600	5.5	4.0	F
2	52500	9.0	4.0	M
3	58900	4.0	5.0	F
4	59000	8.0	4.0	M
5	57500	9.5	5.0	M
6	55500	3.0	4.0	F
7	56000	7.0	3.0	F
8	52700	1.5	4.5	F
9	65000	8.5	5.0	M
10	60000	7.5	6.0	F
11	56000	9.5	2.0	M
12	54900	6.0	2.0	F
13	55000	2.5	4.0	M
14	60500	1.5	4.5	M

1. If a person had six (6) years experience, what would you predict the salary to be?

Select one:

a. 53,878

b. 56,952

c. 51,323

d. 48,200

e. 9,181

2. At the 10% level of significance, would you claim that the data is correlated?

Select one:

a. There is insufficient data to answer this question.

b. No, the data is not correlated.

c. Yes, the data is correlated.

d. I would claim that there is a weak negative relationship between the data.

e. I would claim that there is a strong negative relationship between the data.

Answer 1

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.189746
R Square	0.036004
Adjusted R Square	-0.04433
Standard Error	3540.188
Observations	14
ANOVA
	df	SS	MS	F
Regression	1	5617003.705	5617004	0.44818
Residual	12	150395139.2	12532928
Total	13	156012142.9
	Coefficients	Standard Error	t Stat	P-value
Intercept	55613.5	2189.969313	25.39465	8.45E-12
X Variable 1	223.0234	333.1381424	0.669462	0.515875

The regression equation is:

y = 55613.5 + 223.0234x

y = salary

x= experience

So, if a person has 6 years of experience salary is

y =  55613.5 + 223.0234*6 = 56951.64~56952(b)

2) r = 0.1897

Since t< t_crit so we reject the null hypothesis of no correlation

Hence,

yes the data is correlated.