Data Set for Assignment 4

Could you give some suggestion for question 1 and 2

Occupational Title

Education Level (years)

Income ($)

Percent of Workforce that are Women

Prestige Score

GOV_ADMINISTRATORS

13.11

12351

11.16

68.8

GENERAL_MANAGERS

12.26

25879

4.02

69.1

ACCOUNTANTS

12.77

9271

15.7

63.4

PURCHASING_OFFICERS

11.42

8865

9.11

56.8

CHEMISTS

14.62

8403

11.68

73.5

PHYSICISTS

15.64

11030

5.13

77.6

BIOLOGISTS

15.09

8258

25.65

72.6

ARCHITECTS

15.44

14163

2.69

78.1

CIVIL_ENGINEERS

14.52

11377

1.03

73.1

MINING_ENGINEERS

14.64

11023

0.94

68.8

SURVEYORS

12.39

5902

1.91

62

DRAUGHTSMEN

12.3

7059

7.83

60

COMPUTER_PROGRAMERS

13.83

8425

15.33

53.8

ECONOMISTS

14.44

8049

57.31

62.2

PSYCHOLOGISTS

14.36

7405

48.28

74.9

SOCIAL_WORKERS

14.21

6336

54.77

55.1

LAWYERS

15.77

19263

5.13

82.3

LIBRARIANS

14.15

6112

77.1

58.1

VOCATIONAL_COUNSELLORS

15.22

9593

34.89

58.3

MINISTERS

14.5

4686

4.14

72.8

UNIVERSITY_TEACHERS

15.97

12480

19.59

84.6

PRIMARY_SCHOOL_TEACHERS

13.62

5648

83.78

59.6

SECONDARY_SCHOOL_TEACHERS

15.08

8034

46.8

66.1

PHYSICIANS

15.96

25308

10.56

87.2

VETERINARIANS

15.94

14558

4.32

66.7

OSTEOPATHS_CHIROPRACTORS

14.71

17498

6.91

68.4

NURSES

12.46

4614

96.12

64.7

NURSING_AIDES

9.45

3485

76.14

34.9

PHYSIO_THERAPSTS

13.62

5092

82.66

72.1

PHARMACISTS

15.21

10432

24.71

69.3

MEDICAL_TECHNICIANS

12.79

5180

76.04

67.5

COMMERCIAL_ARTISTS

11.09

6197

21.03

57.2

RADIO_TV_ANNOUNCERS

12.71

7562

11.15

57.6

ATHLETES

11.44

8206

8.13

54.1

SECRETARIES

11.59

4036

97.51

46

TYPISTS

11.49

3148

95.97

41.9

BOOKKEEPERS

11.32

4348

68.24

49.4

TELLERS_CASHIERS

10.64

2448

91.76

42.3

COMPUTER_OPERATORS

11.36

4330

75.92

47.7

SHIPPING_CLERKS

9.17

4761

11.37

30.9

FILE_CLERKS

12.09

3016

83.19

32.7

RECEPTIONSTS

11.04

2901

92.86

38.7

MAIL_CARRIERS

9.22

5511

7.62

36.1

POSTAL_CLERKS

10.07

3739

52.27

37.2

TELEPHONE_OPERATORS

10.51

3161

96.14

38.1

COLLECTORS

11.2

4741

47.06

29.4

CLAIM_ADJUSTORS

11.13

5052

56.1

51.1

TRAVEL_CLERKS

11.43

6259

39.17

35.7

OFFICE_CLERKS

11

4075

63.23

35.6

SALES_SUPERVISORS

9.84

7482

17.04

41.5

COMMERCIAL_TRAVELLERS

11.13

8780

3.16

40.2

SALES_CLERKS

10.05

2594

67.82

26.5

NEWSBOYS

9.62

918

7

14.8

SERVICE_STATION_ATTENDANT

9.93

2370

3.69

23.3

INSURANCE__AGENTS

11.6

8131

13.09

47.3

REAL_ESTATE_SALESMEN

11.09

6992

24.44

47.1

BUYERS

11.03

7956

23.88

51.1

FIREFIGHTERS

9.47

8895

Occupational Title+ Education Level GOV_ADMINISTRATORS+ Income ($)+ (years)+ Percent of Workforce that GENERAL_MANAGERS+ Prestige Score+ 13.114 are Women+ ACCOUNTANTS+ 12351+ 12.26+ 11.164 PURCHASING_OFFICERS 25879+ 68.8+ 4.02+ CHEMISTS+ 12.774 9271+7 69.1+ PHYSICISTS+ 11.42+ 386547 15.7+ 53.4+ 14.62+ 9.114 BIOLOGISTS 8403+ 56 8-7 15.64+ 1030+ 1.68+ 73.5+7 ARCHITECTS+ 15.09+ 5 .13+ 77.6+74 CIVIL_ENGINEERS+ 8258+ 15.44+ 5.65 MINING_ENGINEERS+ 141634 72.647 14.524 2.69+ 1377+ 78.1+47 SURVEYORS+ 14.64+ 1.03+ 73.1+4 DRAUGHTSMEN+ 1023+ 12.394 0.94+7 COMPUTER_PROGRAMERS+ 5902+ 58.847 12.34 1.91+7 70594 62+ ECONOMISTS+ 8425+7 7.83+7 6047 PSYCHOLOGISTS+ 13.8340 14.44+ 15.33+ 80494 53.8+7 SOCIAL_WORKERS+ 14.36+ 57.31+ 62.247 LAWYERS+ 7405+7 14.21+ 48.28+7 LIBRARIANS + 6336+3 74.947 15.77+7 54.77+ 55.1+7 VOCATIONAL_COUNSELLORS+ 19263+ 14.15+7 MINISTERS+ 6112+ 5.13+ 15.22+7 77.1+ 82.3+ 9593+7 58.147 UNIVERSITY_TEACHERS+ 14.5+7 14.894 4686+ 58.3+7 47 PRIMARY_SCHOOL_TEACHERS+7 SECONDARY_SCHOOL_TEACHERS+ 15.97+ 4.14+ 12480+7 72.8+7 13.62+7 5648+ 19.594 PHYSICIANS+ 84. 6+ 7 15.0847 83.78+ 59.6+747 VETERINARIANS+ 8034+ 15.9647 46.8+ OSTEOPATHS_CHIROPRACTORS+ 25308+ 66.1+ 15.94+ 0.56+ NURSES+ 14558+ 87.2+ 14.71+ 4.32+ 66.7+ NURSING_AIDES+ 17498+ 12.46+7 6.91+ 68.4+747 PHYSIO_THERAPSTS+ 4614+7 9.45+7 96.12+ PHARMACISTS+ 3485+7 64.7+ 13.62+ MEDICAL_TECHNICIANS 5092+ 16.14+ 34.947 72.1+ COMMERCIAL_ARTISTS+ 15.214 10432+ 32.66 12.794 24.71+ 518047 69.347 RADIO_TV_ANNOUNCERS+ 76.04+ ATHLETES+ 11.094 6197+7 67.5+7 12.71+ 21.03+ 7562+7 57.2+ SECRETARIES+ 11.15 TYPISTS+ 11.44( 82064 57 .6+7 11.59+ 4036+ 8.13+ 54.147 47 BOOKKEEPERS+ 11.49+ 97.51+ TELLERS_CASHIERS+ 3148+ 11.324 4348+7 95.97 + 41.94347 COMPUTER_OPERATORS+ 10.64+ 68.24+7 SHIPPING_CLERKS+ 2448+ 49.4+74 11.36+ 91.76+ FILE_CLERKS+ 433047 42 3+7 4 9.17+ 75.92+7 4761+7 47.7+4 RECEPTIONSTS+ 12.0943 11.3747 MAIL_CARRIERS+ 3016+7 30.94747 11.04+ 83.19 POSTAL_CLERKS+ 2901+ 32.7+7 9.22+ 5511+ 92.86+ TELEPHONE_OPERATORS+ 10.07+7 7.62+7 38.7+ 36.1+ COLLECTORS+ 37390 10.5147 52.27+7 37.2+ CLAIM_ADJUSTORS+ 3161+ 11.2+ 36.14 TRAVEL_CLERKS+ 4741+7 11.1347 47.0647 38.1+7 5052+7 29.4+7 OFFICE_CLERKS+ 11.43+ 56.1+ 51.1+ + SALES_SUPERVISORS+ 625943 11+ 4075+7 19.17+ 35.7+ + COMMERCIAL_TRAVELLERS+ 9.84 47 63.234 SALES_CLERKS 7482+7 35.6+74 11.13+7 17.04+ 8780+ 41.5+747 NEWSBOYS+ 10.05+ 2594+7 3.16+ 40.247 47 SERVICE_STATION_ATTENDANT+ 9.62+7 918+ 57.82 26.5+7 INSURANCE_AGENTS+7 9.93+7 REAL_ESTATE_SALESMEN+ 11.6+7 237047 14.8+7 4 8131+7 3.6947 BUYERS+ 23.3+747 11.0947 13.0947 FIREFIGHTERS+ 6992+7 47.3+7 11.03+7 7956+7 24.44+7 47.14747 POLICEMEN+ 23.88 COOKS+ 9.47+ 8895+7 51.1+74 10.93+ 889147 0+7 43.547 BARTENDERS+ 7.74+ 1.65+7 51.6+7 FUNERAL_DIRECTORS+ 3116+7 29.7+7 BABYSITTERS+ 8.5+7 393047 10.5747 15.51+ LAUNDERERS+ 86947 20.2+7 9.46+ 6.01+ JANITORS+ 6114 54.947 47 7.33+ 96.53+ 3000+3 25.947 4 ELEVATOR_OPERATORS+ 7.11+7 69.31+ FARMERS+ 3472+ 20.8+7 47 7.58+ 33.57 + 17.3+7 47 FARM_WORKERS+ 3582+7 6.84+7 30.08 3643+7 20.147 4 7 ROTARY_WELL_DRILLERS+ 8.6+ 3.6+ 1656+7 44 .147 4 3.88+ 68600 27.7547 21.547 35.3+7+below. (1) To get a sense of the data, generate a scatterplot to examine the association between prestige score and years of education. Briefly describe the form, direction, and strength of the association between the variables. Calculate the correlation. (3 points )+ (2) Perform a simple linear regression. Generate a residual plot. Assess whether the model assumptions are met. Are there any outliers or influence points? If so, identify them by ID and comment on the effect of each on the regression. (3 points)- (3) Calculate the least squares regression equation that predicts prestige from education, income and percentage of women. Formally test whether the set of these predictors are associated with prestige at the " = 0.05 level. (6 points)- (4) If the overall model was significant, summarize the information about the contribution of each variable separately at the same significance level as used for the overall model (no need to do a formal 5-step procedure for each one, just comment on the results of the tests). Provide interpretations for any estimates that were significant. Calculate 95% confidence intervals where appropriate. (5 points)+ (5) Generate a residual plot showing the fitted values from the regression against the residuals. Is the fit of the model reasonable? Are there any outliers or influence points? (3 points)