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A medium-sized automobile insurance company is interested in developing a regression model to help predict the monthly collision claims of its policyholders. A company analyst

A medium-sized automobile insurance company is interested in developing a regression model to help predict the monthly collision claims of its policyholders. A company analyst has proposed modeling monthly collision claims (y) in the Middle Atlantic states as a function of the percentage of claims by drivers under age 30 (x1) and the average daily temperature during the month (x2). She believes that as the percentage of claims by drivers under age 30 increases, claims will rise because younger drivers are usually involved in more serious accidents than older drivers. She also believes that claims will rise as the average daily temperature decreases because lower temperatures are associated with icy, hazardous driving conditions. In order to develop a preliminary model, data were collected for the state of New Jersey over a 3 year period. The data are in the attached file.

  1. Use a software package to fit the complete second order modelE(y) = 0+1x1+2x2+ 3x1x2+4x12+ 5x22
  2. Test the hypothesis H0: 4=5=0 using alpha = 0.05. Interpret the results in practical terms.
  3. Do the results support the analysts' beliefs? Explain.

Data:

Month:

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

Collition:

116250

217180

43436

159265

130308

72393

174740

101351

144787

28957

173744

86872

108420

203288

40658

149078

121973

67763

163130

94858

135525

27105

162631

81315

114890

217726

43084

157973

129910

71808

172005

103166

143612

28722

175335

87157

154886

290411

58082

212966

174247

96804

230329

136528

193608

38722

212309

118796

PctUnder30:

50

60.8

45.1

56.4

53.3

46.9

57.8

50.6

55

35.8

57.9

49.9

51

62.9

45.1

55.2

53.7

47.2

56.1

48.3

54.7

45.4

56.5

47.7

51.3

61.6

45.9

55.2

53.6

46.9

58.2

51.1

55.4

28.2

57.5

48.2

56.9

66.5

45.9

61.4

57.7

48.9

64.3

53.1

59.8

45.6

63.9

52.3

Temperature:

31.5

33

45

53.9

63.9

74.5

79.4

75.3

68.7

53.7

47.6

38.4

28.7

34.4

43.9

51.1

63.4

73

80.5

79.8

68

52.6

48.9

35.5

37

34.2

42.4

52.5

63.2

74.3

77.2

76.3

69.9

59.1

45

25.6

40.4

39.8

44.9

53.3

61.1

73.4

77.8

76.6

68.6

62.4

50

42.3

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