A researcher working for an insurance company is interested in the effect of driving experience and the number of traffic offences on car insurance premiums. A random sample of 12 drivers yields the following data.

Monthly premium

($)

Driving experience

(years)

Number of traffic offences in the last 3 years

148

5

2

76

14

0

100

6

1

126

10

3

194

4

6

110

8

2

114

11

3

86

16

1

198

3

5

92

9

1

70

19

0

120

13

3

Mean: 119.5

Mean:9.83

Mean:2.25

Multiple regression analysis is undertaken using Excel and the output is reported in the following table.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.964970197

R Square

0.931167481

Adjusted R Square

0.915871366

Standard Error

12.14592045

Observations

12

ANOVA

df

SS

MS

F

Significance F

Regression

2

17961.29

8980.645

60.87608

5.88941E-06

Residual

9

1327.71

147.5234

Total

11

19289

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

110.276072

14.61865

7.54352

3.53E-05

77.206390

143.34575

Driving experience

-2.74727226

0.977006

-2.81193

0.020313

-4.9574137

-0.5371307

Traffic offences

16.1061208

2.61332

6.163089

0.000166

10.194381

22.017860

SHOW YOUR WORKINGS.

A) State the multiple regression model for this data and interpret both slope coefficients.

B) At the 0.01 level of significance test the significance of the coefficient of Driving Experience.

C) At the 0.01 level of significance test the significance of the overall model.