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The images contain data on employee’s perceived appreciation (appr; 1 = very low to 7 = very high), their perceived level of non-salary benefits (e.g., free coffee provision in office, bef; 1 = very negative to 7 = very positive), their satisfaction with the employer (sat; 1 = very dissatisfied to 7 = very satisfied), and the length of their service with the employer (tenure; in years). Based on them , write a problem statement  on analyzing the effects of drivers on employee satisfaction or decline in employee satisfaction. Explain what kind of data is put to use ,and why a regression analysis would be better put to use rather than a variance analysis.

The images contain data on employee’s perceived appreciation (appr; 1 = very low to 7 = very high), their perceived level of non-salary benefits (e.g., free coffee provision in office, bef; 1 = very negative to 7 = very positive), their satisfaction with the employer (sat; 1 = very dissatisfied to 7 = very satisfied), and the length of their service with the employer (tenure; in years). Based on them , write a problem statement  on analyzing the effects of drivers on employee satisfaction or decline in employee satisfaction. Explain what kind of data is put to use ,and why a regression analysis would be better put to use rather than a variance analysis.

College Algebra (MindTap Course List)
College Algebra (MindTap Course List)
12th Edition
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:R. David Gustafson, Jeff Hughes
Chapter8: Sequences, Series, And Probability
Section8.CR: Chapter Review
Problem 78E
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The images contain data on employee’s perceived appreciation (appr; 1 = very low to 7 = very high), their perceived level of non-salary benefits (e.g., free coffee provision in office, bef; 1 = very negative to 7 = very positive), their satisfaction with the employer (sat; 1 = very dissatisfied to 7 = very satisfied), and the length of their service with the employer (tenure; in years).
Based on them , write a problem statement  on analyzing the effects of drivers on employee satisfaction or decline in employee satisfaction. Explain what kind of data is put to use ,and why a regression analysis would be better put to use rather than a variance analysis.

1 2 3 4 LO 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 id 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 appr 4.00 5.67 4.33 3.33 6.00 2.67 6.00 6.33 7.00 6.33 7.00 4.67 1.00 5.00 5.67 5.67 7.00 2.33 5.33 5.67 4.00 5.00 5.00 5.67 7.00 2.00 6.00 6.67 perf 4.50 4.50 1.00 1.00 2.00 1.50 6.00 3.50 2.00 6.50 7.00 2.00 1.50 5.00 1.00 1.00 7.00 1.00 2.00 2.00 4.50 1.00 4.50 1.00 4.00 1.50 4.00 2.00 sat 1.75 4.25 4.50 1.00 2.25 4.50 1.25 1.50 1.50 1.75 4.50 1.50 1.50 2.00 2.00 3.50 4.00 1.00 1.25 3.00 2.75 1.00 1.50 1.50 4.00 1.25 4.75 1.00 BESMETTETTE tenure 1 1 11 1 14 5 1 20 3 1 8 1 17 1 15 15 4 20 7 4 4 4 1 18 6 10 13 21
Transcribed Image Text:1 2 3 4 LO 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 id 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 appr 4.00 5.67 4.33 3.33 6.00 2.67 6.00 6.33 7.00 6.33 7.00 4.67 1.00 5.00 5.67 5.67 7.00 2.33 5.33 5.67 4.00 5.00 5.00 5.67 7.00 2.00 6.00 6.67 perf 4.50 4.50 1.00 1.00 2.00 1.50 6.00 3.50 2.00 6.50 7.00 2.00 1.50 5.00 1.00 1.00 7.00 1.00 2.00 2.00 4.50 1.00 4.50 1.00 4.00 1.50 4.00 2.00 sat 1.75 4.25 4.50 1.00 2.25 4.50 1.25 1.50 1.50 1.75 4.50 1.50 1.50 2.00 2.00 3.50 4.00 1.00 1.25 3.00 2.75 1.00 1.50 1.50 4.00 1.25 4.75 1.00 BESMETTETTE tenure 1 1 11 1 14 5 1 20 3 1 8 1 17 1 15 15 4 20 7 4 4 4 1 18 6 10 13 21
52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 1.00 7.00 4.00 5.33 6.67 5.00 5.33 5.67 1.33 4.67 6.00 5.67 5.00 7.00 5.00 4.00 6.00 4.00 4.67 5.67 4.67 5.00 5.33 5.00 7.00 7.00 4.00 4.00 1.00 2.00 1.00 3.00 1.00 7.00 6.00 5.00 1.00 1.00 2.00 4.50 2.00 7.00 1.00 1.00 3.00 2.50 1.00 3.00 4.00 2.00 3.50 5.00 2.00 1.00 1.00 1.00 1.00 4.50 1.00 1.75 2.25 1.50 3.00 3.75 1.50 3.50 5.25 3.25 1.00 5.75 2.75 1.50 2.75 5.50 1.00 1.00 4.25 1.50 1.50 5.50 2.00 1.50 1.00 1.00 1 12 14 16 6 1 8 3 5 17 22 1 9 14 1 4 12 8 3 1 9 11 4 4 18 6 1 6
Transcribed Image Text:52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 1.00 7.00 4.00 5.33 6.67 5.00 5.33 5.67 1.33 4.67 6.00 5.67 5.00 7.00 5.00 4.00 6.00 4.00 4.67 5.67 4.67 5.00 5.33 5.00 7.00 7.00 4.00 4.00 1.00 2.00 1.00 3.00 1.00 7.00 6.00 5.00 1.00 1.00 2.00 4.50 2.00 7.00 1.00 1.00 3.00 2.50 1.00 3.00 4.00 2.00 3.50 5.00 2.00 1.00 1.00 1.00 1.00 4.50 1.00 1.75 2.25 1.50 3.00 3.75 1.50 3.50 5.25 3.25 1.00 5.75 2.75 1.50 2.75 5.50 1.00 1.00 4.25 1.50 1.50 5.50 2.00 1.50 1.00 1.00 1 12 14 16 6 1 8 3 5 17 22 1 9 14 1 4 12 8 3 1 9 11 4 4 18 6 1 6
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