21 22 Stocks Geography Get External Data Filter Refresh All AL Sort 19 Q31 63 63 62 60 x D Father Gelehre Gather Part 1 78 72 71 Life insurance companies are keenly interested in predicting how long 76 66 their customers will live, because their premiums and profitability depend 73 67 37 67 6 55 on such numbers. Data were gathered for 100 deceased males, in order 73 646 73 to formulate a regression that predicted longevity based on: 72 74 62 . Age at death of the two parents 70 59 Mean age at death of grandfather and grandmothers 71 74 61 75 71 Questions 64 76 61 a. Perform a multiple regression analysis and show the prediction 66 61 equation, based on the data in "Longevity": 76 73 b. is the model useful at 2.5% significance level? 77 69 68 c. Interpret the coefficients b1 and b2 in this model. 06 67 67 70 71 67 Part 2 (see Longevity (2) 66 57 A statistician working for the company suggeted smoking is a major 71 determinant of a person's longevityl see the sheet "Longevity (2)"). He 71 added this variable as a predictor to the first group of independent variables, but at the same time took out the insignificant variables from the previous model of Part 1. Questions 80 d. Run the reduced model (that now includes only three independant 77 variavles), and show the prediction equation e Interpret the coefficient of the predictor "Smoker" in this model. What does its value mean in this model? 1. A smoker, whose both parents passed at the age of 85, is 62 years old. 75 69 How many more years is he expected to live? g. His friend is not a smoker who lost his mother when she was 70 years old, and father when he was 60 years old. How long is he expected to 72 62 live? 72 h. Can you determine with 90% confidence which of the two friends will die at a younger age? 63 03 75 60 66 66 61 63 64 65 62 62 69 65 71 61 67 A 1 Longevity Mother NO 85 73 8 4 70 66 5 72 72 6 79 90 70 67 9 72 76 66 11 91 78 13 67 69 11 74 71 80 74 13 63 68 16 71 70 17 66 54 IN 74 19 71 71 20 65 75 21 74 76 2 66 69 71 76 24 73 69 25 74 79 26 68 74 29 77 81 77 85 29 74 77 JO 68 72 31 68 75 12 74 82 33 71 73 34 80 84 15 72 75 16 77 37 76 88 3 62 65 39 70 75 40 71 72 41 69 72 42 73 79 43 72 72 44 84 80 45 73 76 46 70 78 47 78 75 48 82 83 49 77 75 50 67 68 51 72 69 SZ 67 67 60 63 59 73 HO 62 65 70 62 78 69 69 71 65 66 72 65 73 61 68 77 77 71 76 69 75 SUMMARY OUTPUT 57 57 67 60 71 69 90 74 70 74 78 66 68 67 67 68 74 72 72 69 78 67 57 57 64 67 65 65 71 65 54 70 65 Regression Statistics Multiple R 0.860843 R Square 0.74105 Adjusted 0.730147 Standard E 2.664075 Observati 100 58 77 72 60 ANOVA 69 62 oly 72 67 73 69 72 Regression Residual SS MS 4 1929.517 482.3792 67.96663 95 674.243 7.097295 P53 Y $) 78 73 TI 73 84 30 OG 33 X STORE SOS 56 57 SN 39 99 61 72 75 72 75 SO 72 71 71 89 74 72 74 77 77 73 19 19 09 19 71 72 6 70 72 7 RS 72 74 73 74 20 71 67 72 72 68 72 65 66 68 77 72 71 64 68 65 5329 65 74 72 73 63 65 0 69 60 4 $99 ERRER 66 64 67 0 19 95 ES 76 64 72 69 59 69 76 63 66 72 68 23 76 83 1.73 69 53 61 67 79 80 67 62 69 65 54 654 60 66 75 72 82 73 75 59 73 2 71 74 35 72 30 82 82 R2 73 27 74 BO 76 68 CN EN 72 72 su 85 R83 772 72 61 72 67 65 67 71 76 76 65 GO 72 75 69 71 20 66 73 20 66 87 59 79 63 72 60 64 9 90 91 92 93 94 90 68 66 75 71 73 71 77 67 68 67 9 77 76 68 71 76 67 74 08 61 62 64 68 66 20 57 64 62 69 99 99 19 99 ENS SES Longevity Longevity (2) Data All 16 J13 fx A T 11 1 K 1 16 99 5 Leng Me HO 85 73 TO 66 72 70 38 33 90 70 67 12 72 46 71 7 7 65 19 11 Seke No Ya Y Yo Ne N Yus Yet Y Yes Ne Ne Ya Yel Yes No Yes You No Yes [i 74 RO 61 c D Funer Cheather Com 70 72 70 75 62 17 55 55 33 73 74 62 49 70 21 74 29 63 44 76 61 66 61 69 76 73 60 68 66 67 62 70 62 66 63 57 71 75 65 71 63 63 62 66 68 61 65 07 63 71 80 54 63 70 77 03 59 03 73 03 TI 24 70 TG 13 18 17 1 10 20 21 21 06 74 71 65 74 09 99 69 9 71 11 74 11 75 76 69 76 69 79 74 81 07 25 26 22 38 20 30 69 71 ON SL EL 66 72 75 65 59 33 27 77 74 68 68 74 71 RD 72 777 76 62 71 Yes No Yes No No Yes Yes Yes No Yes No Ya No No Yes Yes Yes LE PE 73 14 75 19 19 6 72 13 01 76 69 53 57 67 6) 21 30 37 67 31 BE 65 735 30 40 41 6 72 77 71 75 68 67 67 68 74 22 22 69 28 79 69 65 65 ( 69 Yes Yes No 90 45 45 47 40 41 MOORREESEEN 30 76 78 25 83 75 63 70 74 71 69 72 Na Na No Yel Ver Yes 72 73 69 72 67 71 71 65 54 70 65 60 62 6N 66 66 61 68 59 94 61 31 33 33 34 35 59 37 67 T! No 19 71 73 14 73 66 71 66 Ne Ya Longevity Longevity (2) + Home ICH 21 Get External Data Stocks Refresh All Geography Sort Filter J115 . 1 F 11 1 1 1 N 0 6 78 4 72 TI 2 64 61 70 27 71 74 77 16 7 23 TE 55 73 67 14 1 3 ED SERESSE 74 77 68 97 72 73 64 si 41 61 67 77 63 22 71 54 7 62 60 49 60 73 (9 72 5 31 76 70 67 99 22 33 TB 35 99 19 57 69 59 69 76 25 Yar Y Yu Ne Ne Yo Na No No Y Y Yes No NO Ya Ya Yes Yes Yes Ne Yer Yel Yes Y Yes Ne N NO Ya Yes Yes Ye No 67 65 56 TE 2 71 LY 4 60 6 72 72 61 72 67 65 67 TI 76 76 65 56 33 60 30 6) 67 19 09 VE 72 6 73 11 RE 39 23 73 10 82 22 57 72 RS T! 67 70 61 75 72 2 70 62 60 79 64 59 67 65 75 06 TE 66 FY 99 16 72 75 60 71 70 06 NE 71 72 94 30 16 71 27 16 75 68 71 T6 27 66 72 60 66 67 74 FE sh 69 54 70 57 64 19 71 22 61 65 &? 94 70 72 67 FL OL 99 99 LE 61 63 Ya Yes Ne Yes You Ye No Yes Yes Yea 33 46 59 66 64 300 TO 201 70 60 21 74 73 LO 164 10 109 110 114 0151 Longevity Longevity (2) + K L M N R Gmother & Gfather Part 1 Life Insurance companies are keenly interested in predicting how long their customers will live, because their premiums and profitability depend on such numbers. Data were gathered for 100 deceased males, in order to formulate a regression that predicted longevity based on: Age at death of the two parents * Mean age at death of grandfather and grandmothers Questions a. Perform a multiple regression analysis and show the prediction equation, based on the data in "Longevity". b. Is the model useful at 2.5% significance level? c. Interpret the coefficients b1 and b2 in this model. Part 2 (see Longevity (2) A statistician working for the company suggeted smoking is a major determinant of a person's longevity( see the sheet "Longevity (2)"). He added this variable as a predictor to the first group of independent variables, but at the same time took out the insignificant variables from the previous model of Part 1. Questions d. Run the reduced model (that now includes only three independant variavles), and show the prediction equation. e. Interpret the coefficient of the predictor "Smoker" in this model. What does its value mean in this model? f. A smoker, whose both parents passed at the age of 85, is 62 years old How many more years is he expected to live? 8. His friend is not a smoker who lost his mother when she was 70 years old, and father when he was 60 years old. How long is he expected to live? h. Can you determine with 90% confidence which of the two friends will die at a younger age? F G H Smoker No Yes 1 Longevity Mother 2 BO 85 3 73 88 4 70 66 72 72 6 79 88 7 83 90 8 70 67 9 72 76 10 72 66 11 71 78 12 67 69 13 74 71 80 74 15 63 68 16 71 70 17 66 64 18 74 82 19 71 71 20 65 75 21 74 76 66 69 23 71 76 73 69 25 74 79 26 68 74 27 77 81 28 77 85 29 74 77 30 68 72 31 68 75 32 74 82 33 71 73 34 80 84 35 72 75 36 77 82 37 76 88 3B 62 65 39 70 75 40 71 72 41 69 72 42 73 79 43 72 77 84 80 45 73 76 46 70 78 47 78 75 48 82 83 49 77 75 SO 67 c D E Father Gmothers Gfathers 78 72 71 63 76 66 75 67 57 67 68 73 64 73 72 74 62 65 70 59 71 74 61 75 71 63 64 76 61 66 61 69 76 73 60 77 69 68 66 67 67 70 71 67 66 63 57 71 75 65 71 68 62 60 63 62 66 66 69 68 61 65 67 63 71 80 64 61 70 77 60 62 59 63 78 73 62 69 80 65 69 75 69 71 72 66 63 65 65 66 72 62 72 68 71 73 77 68 61 77 61 76 71 63 69 75 67 57 68 57 57 67 67 67 64 63 68 67 71 74 65 69 72 65 90 72 71 74 69 65 70 78 54 74 58 70 78 77 65 66 72 60 78 62 Yes Yes No No Yes Yes Yes Yes Yes No No Yes Yes Yes No Yes Yes No Yes Yes Yes No Yes No No Yes Yes Yes No Yes No Yes No No Yes Yes Yes Yes Yes Yes No Yes Yes No No No Yes S84 x B D F G H 67 64 69 66 73 75 53 $4 55 56 37 38 59 60 61 62 63 644 65 67 78 73 71 73 84 78 76 77 86 79 72 78 83 61 70 77 71 77 68 77 E 66 66 61 68 59 74 61 61 61 69 77 68 72 71 64 69 62 Yes Yes No Yes No No Yes Yes Yes No No Yes No No No Yes Yes Yes No No Yes Yes Yes Yes 69 60 66 67 69 70 71 72 73 74 75 76 77 78 79 80 81 82 72 71 71 89 74 72 74 77 77 73 72 65 81 76 64 72 69 59 69 76 63 66 72 68 73 78 83 78 67 70 68 66 75 71 72 71 77 67 68 67 74 70 72 69 Yes 72 67 71 68 66 71 66 74 73 74 70 71 67 77 63 65 74 72 73 63 66 64 60 68 72 72 61 72 67 65 67 71 76 76 65 69 72 75 69 71 70 66 73 70 66 66 66 63 71 67 74 66 82 80 71 73 75 59 73 82 71 74 85 72 80 82 82 82 73 77 74 80 76 71 77 76 79 68 71 76 77 66 78 73 84 85 86 87 88 89 90 91 92 93 94 95 96 97 63 77 70 67 69 67 62 69 65 56 64 60 66 75 72 82 70 62 60 79 63 72 60 64 67 74 68 61 62 64 68 70 60 No Yes Yes Yes Yes Yes No No No Yes Yes Yes Yes No Yes Yes Yes No Yes Yes Yes No Yes Yes Yes 64 66 69 64 70 57 64 62 69 66 64 99 100 101 21 22 Stocks Geography Get External Data Filter Refresh All AL Sort 19 Q31 63 63 62 60 x D Father Gelehre Gather Part 1 78 72 71 Life insurance companies are keenly interested in predicting how long 76 66 their customers will live, because their premiums and profitability depend 73 67 37 67 6 55 on such numbers. Data were gathered for 100 deceased males, in order 73 646 73 to formulate a regression that predicted longevity based on: 72 74 62 . Age at death of the two parents 70 59 Mean age at death of grandfather and grandmothers 71 74 61 75 71 Questions 64 76 61 a. Perform a multiple regression analysis and show the prediction 66 61 equation, based on the data in "Longevity": 76 73 b. is the model useful at 2.5% significance level? 77 69 68 c. Interpret the coefficients b1 and b2 in this model. 06 67 67 70 71 67 Part 2 (see Longevity (2) 66 57 A statistician working for the company suggeted smoking is a major 71 determinant of a person's longevityl see the sheet "Longevity (2)"). He 71 added this variable as a predictor to the first group of independent variables, but at the same time took out the insignificant variables from the previous model of Part 1. Questions 80 d. Run the reduced model (that now includes only three independant 77 variavles), and show the prediction equation e Interpret the coefficient of the predictor "Smoker" in this model. What does its value mean in this model? 1. A smoker, whose both parents passed at the age of 85, is 62 years old. 75 69 How many more years is he expected to live? g. His friend is not a smoker who lost his mother when she was 70 years old, and father when he was 60 years old. How long is he expected to 72 62 live? 72 h. Can you determine with 90% confidence which of the two friends will die at a younger age? 63 03 75 60 66 66 61 63 64 65 62 62 69 65 71 61 67 A 1 Longevity Mother NO 85 73 8 4 70 66 5 72 72 6 79 90 70 67 9 72 76 66 11 91 78 13 67 69 11 74 71 80 74 13 63 68 16 71 70 17 66 54 IN 74 19 71 71 20 65 75 21 74 76 2 66 69 71 76 24 73 69 25 74 79 26 68 74 29 77 81 77 85 29 74 77 JO 68 72 31 68 75 12 74 82 33 71 73 34 80 84 15 72 75 16 77 37 76 88 3 62 65 39 70 75 40 71 72 41 69 72 42 73 79 43 72 72 44 84 80 45 73 76 46 70 78 47 78 75 48 82 83 49 77 75 50 67 68 51 72 69 SZ 67 67 60 63 59 73 HO 62 65 70 62 78 69 69 71 65 66 72 65 73 61 68 77 77 71 76 69 75 SUMMARY OUTPUT 57 57 67 60 71 69 90 74 70 74 78 66 68 67 67 68 74 72 72 69 78 67 57 57 64 67 65 65 71 65 54 70 65 Regression Statistics Multiple R 0.860843 R Square 0.74105 Adjusted 0.730147 Standard E 2.664075 Observati 100 58 77 72 60 ANOVA 69 62 oly 72 67 73 69 72 Regression Residual SS MS 4 1929.517 482.3792 67.96663 95 674.243 7.097295 P53 Y $) 78 73 TI 73 84 30 OG 33 X STORE SOS 56 57 SN 39 99 61 72 75 72 75 SO 72 71 71 89 74 72 74 77 77 73 19 19 09 19 71 72 6 70 72 7 RS 72 74 73 74 20 71 67 72 72 68 72 65 66 68 77 72 71 64 68 65 5329 65 74 72 73 63 65 0 69 60 4 $99 ERRER 66 64 67 0 19 95 ES 76 64 72 69 59 69 76 63 66 72 68 23 76 83 1.73 69 53 61 67 79 80 67 62 69 65 54 654 60 66 75 72 82 73 75 59 73 2 71 74 35 72 30 82 82 R2 73 27 74 BO 76 68 CN EN 72 72 su 85 R83 772 72 61 72 67 65 67 71 76 76 65 GO 72 75 69 71 20 66 73 20 66 87 59 79 63 72 60 64 9 90 91 92 93 94 90 68 66 75 71 73 71 77 67 68 67 9 77 76 68 71 76 67 74 08 61 62 64 68 66 20 57 64 62 69 99 99 19 99 ENS SES Longevity Longevity (2) Data All 16 J13 fx A T 11 1 K 1 16 99 5 Leng Me HO 85 73 TO 66 72 70 38 33 90 70 67 12 72 46 71 7 7 65 19 11 Seke No Ya Y Yo Ne N Yus Yet Y Yes Ne Ne Ya Yel Yes No Yes You No Yes [i 74 RO 61 c D Funer Cheather Com 70 72 70 75 62 17 55 55 33 73 74 62 49 70 21 74 29 63 44 76 61 66 61 69 76 73 60 68 66 67 62 70 62 66 63 57 71 75 65 71 63 63 62 66 68 61 65 07 63 71 80 54 63 70 77 03 59 03 73 03 TI 24 70 TG 13 18 17 1 10 20 21 21 06 74 71 65 74 09 99 69 9 71 11 74 11 75 76 69 76 69 79 74 81 07 25 26 22 38 20 30 69 71 ON SL EL 66 72 75 65 59 33 27 77 74 68 68 74 71 RD 72 777 76 62 71 Yes No Yes No No Yes Yes Yes No Yes No Ya No No Yes Yes Yes LE PE 73 14 75 19 19 6 72 13 01 76 69 53 57 67 6) 21 30 37 67 31 BE 65 735 30 40 41 6 72 77 71 75 68 67 67 68 74 22 22 69 28 79 69 65 65 ( 69 Yes Yes No 90 45 45 47 40 41 MOORREESEEN 30 76 78 25 83 75 63 70 74 71 69 72 Na Na No Yel Ver Yes 72 73 69 72 67 71 71 65 54 70 65 60 62 6N 66 66 61 68 59 94 61 31 33 33 34 35 59 37 67 T! No 19 71 73 14 73 66 71 66 Ne Ya Longevity Longevity (2) + Home ICH 21 Get External Data Stocks Refresh All Geography Sort Filter J115 . 1 F 11 1 1 1 N 0 6 78 4 72 TI 2 64 61 70 27 71 74 77 16 7 23 TE 55 73 67 14 1 3 ED SERESSE 74 77 68 97 72 73 64 si 41 61 67 77 63 22 71 54 7 62 60 49 60 73 (9 72 5 31 76 70 67 99 22 33 TB 35 99 19 57 69 59 69 76 25 Yar Y Yu Ne Ne Yo Na No No Y Y Yes No NO Ya Ya Yes Yes Yes Ne Yer Yel Yes Y Yes Ne N NO Ya Yes Yes Ye No 67 65 56 TE 2 71 LY 4 60 6 72 72 61 72 67 65 67 TI 76 76 65 56 33 60 30 6) 67 19 09 VE 72 6 73 11 RE 39 23 73 10 82 22 57 72 RS T! 67 70 61 75 72 2 70 62 60 79 64 59 67 65 75 06 TE 66 FY 99 16 72 75 60 71 70 06 NE 71 72 94 30 16 71 27 16 75 68 71 T6 27 66 72 60 66 67 74 FE sh 69 54 70 57 64 19 71 22 61 65 &? 94 70 72 67 FL OL 99 99 LE 61 63 Ya Yes Ne Yes You Ye No Yes Yes Yea 33 46 59 66 64 300 TO 201 70 60 21 74 73 LO 164 10 109 110 114 0151 Longevity Longevity (2) + K L M N R Gmother & Gfather Part 1 Life Insurance companies are keenly interested in predicting how long their customers will live, because their premiums and profitability depend on such numbers. Data were gathered for 100 deceased males, in order to formulate a regression that predicted longevity based on: Age at death of the two parents * Mean age at death of grandfather and grandmothers Questions a. Perform a multiple regression analysis and show the prediction equation, based on the data in "Longevity". b. Is the model useful at 2.5% significance level? c. Interpret the coefficients b1 and b2 in this model. Part 2 (see Longevity (2) A statistician working for the company suggeted smoking is a major determinant of a person's longevity( see the sheet "Longevity (2)"). He added this variable as a predictor to the first group of independent variables, but at the same time took out the insignificant variables from the previous model of Part 1. Questions d. Run the reduced model (that now includes only three independant variavles), and show the prediction equation. e. Interpret the coefficient of the predictor "Smoker" in this model. What does its value mean in this model? f. A smoker, whose both parents passed at the age of 85, is 62 years old How many more years is he expected to live? 8. His friend is not a smoker who lost his mother when she was 70 years old, and father when he was 60 years old. How long is he expected to live? h. Can you determine with 90% confidence which of the two friends will die at a younger age? F G H Smoker No Yes 1 Longevity Mother 2 BO 85 3 73 88 4 70 66 72 72 6 79 88 7 83 90 8 70 67 9 72 76 10 72 66 11 71 78 12 67 69 13 74 71 80 74 15 63 68 16 71 70 17 66 64 18 74 82 19 71 71 20 65 75 21 74 76 66 69 23 71 76 73 69 25 74 79 26 68 74 27 77 81 28 77 85 29 74 77 30 68 72 31 68 75 32 74 82 33 71 73 34 80 84 35 72 75 36 77 82 37 76 88 3B 62 65 39 70 75 40 71 72 41 69 72 42 73 79 43 72 77 84 80 45 73 76 46 70 78 47 78 75 48 82 83 49 77 75 SO 67 c D E Father Gmothers Gfathers 78 72 71 63 76 66 75 67 57 67 68 73 64 73 72 74 62 65 70 59 71 74 61 75 71 63 64 76 61 66 61 69 76 73 60 77 69 68 66 67 67 70 71 67 66 63 57 71 75 65 71 68 62 60 63 62 66 66 69 68 61 65 67 63 71 80 64 61 70 77 60 62 59 63 78 73 62 69 80 65 69 75 69 71 72 66 63 65 65 66 72 62 72 68 71 73 77 68 61 77 61 76 71 63 69 75 67 57 68 57 57 67 67 67 64 63 68 67 71 74 65 69 72 65 90 72 71 74 69 65 70 78 54 74 58 70 78 77 65 66 72 60 78 62 Yes Yes No No Yes Yes Yes Yes Yes No No Yes Yes Yes No Yes Yes No Yes Yes Yes No Yes No No Yes Yes Yes No Yes No Yes No No Yes Yes Yes Yes Yes Yes No Yes Yes No No No Yes S84 x B D F G H 67 64 69 66 73 75 53 $4 55 56 37 38 59 60 61 62 63 644 65 67 78 73 71 73 84 78 76 77 86 79 72 78 83 61 70 77 71 77 68 77 E 66 66 61 68 59 74 61 61 61 69 77 68 72 71 64 69 62 Yes Yes No Yes No No Yes Yes Yes No No Yes No No No Yes Yes Yes No No Yes Yes Yes Yes 69 60 66 67 69 70 71 72 73 74 75 76 77 78 79 80 81 82 72 71 71 89 74 72 74 77 77 73 72 65 81 76 64 72 69 59 69 76 63 66 72 68 73 78 83 78 67 70 68 66 75 71 72 71 77 67 68 67 74 70 72 69 Yes 72 67 71 68 66 71 66 74 73 74 70 71 67 77 63 65 74 72 73 63 66 64 60 68 72 72 61 72 67 65 67 71 76 76 65 69 72 75 69 71 70 66 73 70 66 66 66 63 71 67 74 66 82 80 71 73 75 59 73 82 71 74 85 72 80 82 82 82 73 77 74 80 76 71 77 76 79 68 71 76 77 66 78 73 84 85 86 87 88 89 90 91 92 93 94 95 96 97 63 77 70 67 69 67 62 69 65 56 64 60 66 75 72 82 70 62 60 79 63 72 60 64 67 74 68 61 62 64 68 70 60 No Yes Yes Yes Yes Yes No No No Yes Yes Yes Yes No Yes Yes Yes No Yes Yes Yes No Yes Yes Yes 64 66 69 64 70 57 64 62 69 66 64 99 100 101