Each Excel project file has two tabs DATA and Variable INFO The DATA worksheet contains a YELLOW column representing the numerical response variable and a DARK ORANGE column representing the numerical predictor variable for this simple regression analysis Use only these two columns for this part (Part 1) of the project Introduction Assume you are part of the organization or group that uses the data available to you for your team project Using the YELLOW highlighted numerical variable column in your Excel worksheet as the response variable of interest, Develop an introductory scenario of one paragraph that describes the data file for your project and why you (the Corporation Group) are performing this simple regression analysis that will enable you to predict the outcomes of this numerical response variable based on one predictor variable, the DARK ORANGE column Background Using both the response variable (YELLOW column) and the predictor variable (DARK ORANGE column) develop appropriate descriptive summary measures reviewed in Module 1 Simple Regression Modeling Steps Open the Excel worksheet containing your Team Project Data As you learned in Module 2, run a simple linear regression model using the independent numerical variable whose Excel worksheet column is highlighted in DARK ORANGE as the predictor of Y the YELLOW Excel column Cut and paste into your report the scatter plot and the Excel Regression Output for this simple linear regression model Write the sample regression equation Interpret the meaning of the Y intercept and slope for your fitted model Interpret the meaning of the coefficient of determination r 2 Interpret the meaning of the standard error of the estimate S YX Obtain the residual plots and cut and paste them into the report Briefly comment on the appropriateness of your fitted model (1) If the assumptions are met and the fitted model is appropriate,continue to Step 2G (2) If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step 2G Note you do not need to check the assumption of independence in your project (That assumption is automatically met because your project is not time dependent) Comment on the statistical significance of your fitted model Comment on the 95 confidence interval estimate on the average impact on the response variable for each unit increase in the predictor variable Select a value for your independent variable in its relevant range Predict Salary WorkHrs Age EmpYears VacationBenefitCode VacationBenefit Label 125 3 55 35 3 0 1 Yes 64 8 40 33 9 0 1 Yes 32 3 40 23 1 5 0 No 57 1 40 60 20 0 0 No 97 3 50 39 5 0 0 No 61 4 30 35 3 0 1 Yes 122 6 60 49 5 0 1 Yes 44 0 40 49 22 1 0 No 102 7 44 39 0 5 1 Yes 42 6 40 59 1 5 0 No 53 0 40 25 1 0 1 Yes 20 8 50 20 1 0 0 No 53 3 30 33 5 0 1 Yes 54 1 55 30 5 0 1 Yes 40 3 45 43 12 0 0 No 68 3 40 35 0 5 1 Yes 23 5 40 35 0 8 0 No 26 2 45 41 2 0 0 No 42 1 40 40 10 0 0 No 77 9 50 38 15 0 1 Yes 29 4 35 41 1 0 0 No 24 6 40 32 0 2 0 No 85 9 48 58 36 0 1 Yes 21 4 45 18 1 0 0 No 121 0 50 39 3 0 1 Yes 44 2 40 31 4 0 1 Yes 58 1 45 33 4 0 1 Yes 48 5 32 36 4 1 0 No 66 4 62 28 5 0 1 Yes 51 5 40 25 2 0 0 No 36 0 40 27 5 0 0 No 32 2 40 40 11 8 1 Yes 81 0 50 53 10 0 1 Yes 90 7 72 47 5 0 0 No 26 4 30 27 0 5 0 No 69 3 40 35 10 0 0 No 35 2 40 25 2 5 1 Yes 20 3 35 53 5 0 0 No 66 1 40 35 6 4 1 Yes 86 7 48 43 11 0 1 Yes 80 0 40 48 21 0 0 No 37 8 55 29 1 0 1 Yes 62 4 40 53 0 1 0 No 49 4 40 43 2 0 0 No 51 7 40 30 10 0 0 No 28 6 40 27 0 5 0 No 63 7 35 59 6 0 1 Yes 87 4 40 52 21 0 1 Yes 30 1 50 40 1 5 1 Yes 63 4 59 29 2 8 0 No 124 8 40 40 4 3 1 Yes 103 2 45 38 4 0 1 Yes 65 3 40 52 0 1 0 No 62 7 50 29 1 0 0 No 33 8 42 34 10 0 1 Yes 45 4 50 25 3 0 0 No 24 0 40 32 1 0 0 No 46 7 32 39 2 0 0 No 36 8 40 32 3 0 0 No 32 0 40 25 2 0 1 Yes 42 9 40 37 16 0 0 No 21 5 40 23 1 0 0 No 38 2 41 29 3 0 1 Yes 30 2 50 33 1 0 1 Yes 58 1 44 26 2 5 0 No 82 9 35 44 22 0 0 No 35 4 32 25 1 0 1 Yes 36 0 40 41 10 5 0 No 61 1 40 26 1 0 0 No 59 7 55 27 2 0 0 No 82 9 40 65 12 4 0 No 68 0 40 44 11 0 0 No 71 0 55 48 5 7 0 No 80 8 50 37 8 5 1 Yes 130 7 70 52 1 0 1 Yes 88 5 60 38 2 7 1 Yes 68 2 43 34 5 5 1 Yes 67 7 52 34 13 0 1 Yes 36 0 46 23 1 4 0 No 75 4 50 62 52 3 1 Yes 62 6 76 41 27 2 1 Yes 23 8 38 26 0 5 1 Yes 53 0 40 37 19 0 1 Yes 34 7 40 33 1 0 1 Yes 25 8 54 20 3 0 1 Yes 48 6 60 31 12 5 0 No 45 8 50 28 4 6 0 No 40 3 40 22 1 0 1 Yes 49 0 40 36 7 0 1 Yes 49 4 67 51 32 3 1 Yes 56 2 44 48 24 8 0 No 42 7 48 35 12 0 1 Yes 36 3 38 38 2 7 1 Yes 43 4 40 40 3 0 0 No 72 5 52 32 13 0 0 No 54 4 40 33 11 0 0 No 92 5 60 39 17 0 0 No 72 5 52 47 8 0 0 No 61 0 40 50 22 5 0 No 23 5 50 24 1 0 0 No 56 8 40 30 1 5 0 No 77 8 60 31 3 0 0 No 71 7 60 37 3 0 1 Yes 64 2 50 41 6 0 1 Yes 82 2 55 46 7 0 1 Yes 47 8 49 57 34 0 1 Yes 37 9 32 61 40 0 0 No 42 2 40 58 3 9 0 No 49 3 40 49 6 0 0 No 73 1 40 32 7 0 0 No 76 3 60 32 12 0 1 Yes 62 4 40 44 22 0 1 Yes 51 8 55 34 4 0 1 Yes 49 9 60 38 15 0 1 Yes 26 2 42 30 1 5 0 No 41 8 40 29 0 3 0 No 94 9 50 47 23 6 1 Yes 67 7 70 40 2 0 1 Yes 43 0 40 37 5 0 0 No 61 3 89 44 0 7 1 Yes 94 9 50 39 11 0 1 Yes 26 1 72 41 18 0 1 Yes 55 0 40 30 11 0 0 No 50 2 65 58 3 0 0 No 86 1 75 55 29 0 1 Yes 42 2 68 60 10 0 0 No 37 0 38 41 12 0 0 No 25 2 48 35 7 0 0 No 36 5 50 24 3 0 0 No 49 1 45 39 9 0 0 No 73 3 45 41 8 0 0 No 47 2 60 38 4 0 0 No 41 4 45 29 3 0 0 No 42 9 40 38 7 0 1 Yes 65 9 40 33 10 0 1 Yes 41 6 60 25 3 0 1 Yes 30 4 45 62 23 0 0 No 21 0 40 42 12 8 0 No 30 9 56 33 4 5 1 Yes 33 8 57 27 0 3 0 No 58 6 47 42 5 0 1 Yes 46 9 60 28 5 5 1 Yes 30 9 40 46 2 0 0 No 69 8 46 40 18 0 1 Yes 24 5 40 56 1 8 1 Yes 23 0 40 30 6 0 0 No 48 5 50 44 15 0 0 No 84 3 80 48 9 0 0 No 73 1 40 39 16 0 0 No 25 9 60 39 3 3 1 Yes 71 5 40 62 27 0 1 Yes 29 0 72 21 1 1 0 No 88 0 40 62 1 9 0 No 44 0 45 34 2 1 1 Yes 40 3 40 35 13 0 0 No 34 2 45 41 0 3 0 No 25 8 40 54 33 0 0 No 51 0 40 51 6 0 0 No 80 6 40 52 31 9 1 Yes 25 9 60 29 5 0 0 No 87 8 50 40 6 0 0 No 81 4 45 31 0 7 1 Yes 41 8 40 40 15 0 1 Yes 92 8 48 64 29 0 0 No 52 8 40 52 20 0 0 No 42 6 40 38 11 0 0 No 33 3 40 26 1 5 0 No 34 1 40 45 0 6 1 Yes 65 9 55 33 7 0 1 Yes 62 7 40 36 18 0 0 No 82 6 60 36 5 0 0 No 44 0 50 45 17 0 0 No 81 9 50 54 5 0 1 Yes 122 2 32 57 34 0 1 Yes 31 2 54 43 13 0 0 No 68 5 50 54 27 0 0 No 23 5 40 43 26 0 1 Yes 32 6 40 44 2 0 0 No 61 6 40 39 10 0 0 No 58 6 40 41 11 0 1 Yes 49 9 40 37 5 0 1 Yes 48 6 40 50 23 0 1 Yes 74 6 40 48 25 0 1 Yes 107 2 50 53 11 0 1 Yes 63 0 52 38 1 5 1 Yes 147 0 45 63 32 0 0 No 69 8 40 44 20 0 1 Yes 36 0 50 30 8 0 1 Yes 50 9 40 62 17 0 0 No 44 6 60 38 12 0 0 No 40 0 40 52 27 0 0 No 59 0 48 38 18 0 0 No 68 3 44 55 14 0 1 Yes 60 3 60 43 17 0 1 Yes 84 2 73 25 2 5 1 Yes 52 0 40 53 22 0 1 Yes 75 5 40 32 1 0 1 Yes 59 0 60 40 11 3 1 Yes 21 1 75 28 3 0 1 Yes 36 0 50 52 19 2 1 Yes 37 3 50 39 3 4 0 No 28 5 60 38 2 0 1 Yes 49 8 50 27 3 0 0 No 26 4 80 32 1 5 0 No 34 9 60 51 8 0 1 Yes 75 0 50 42 14 0 1 Yes 21 9 40 30 8 0 0 No 77 4 35 39 9 0 1 Yes 28 0 55 43 5 0 1 Yes 23 8 56 43 0 3 0 No 44 8 56 43 5 5 1 Yes 35 0 50 49 1 5 1 Yes 65 8 50 63 25 0 0 No 49 9 84 33 13 9 0 No 35 2 40 21 1 3 0 No 32 3 42 63 9 4 0 No 20 2 50 36 9 7 0 No 24 3 70 28 9 7 1 Yes 25 3 40 43 18 2 0 No 34 1 34 44 4 0 1 Yes 28 2 63 25 4 0 1 Yes 61 6 65 22 1 0 0 No 54 2 40 47 19 0 0 No 36 2 40 47 10 0 0 No 50 2 65 41 5 0 0 No 30 9 40 35 8 0 0 No 21 3 40 34 13 0 0 No 77 4 80 32 6 0 1 Yes 36 0 50 44 24 0 1 Yes 65 8 45 42 19 3 0 No 23 2 40 22 1 3 0 No 58 1 40 35 16 0 0 No 84 5 60 35 3 0 1 Yes 41 1 30 64 11 0 0 No 40 3 50 33 4 0 0 No 24 0 40 37 1 5 0 No 28 8 40 25 1 5 0 No 49 6 32 35 1 5 1 Yes 53 3 40 34 6 0 0 No 25 3 40 50 10 0 0 No 51 2 40 61 0 8 0 No 57 1 64 37 3 0 1 Yes 38 9 49 24 5 0 0 No 57 8 40 56 30 0 0 No 37 9 40 42 5 5 1 Yes 50 1 48 34 3 0 1 Yes 38 6 42 50 3 5 1 Yes 48 5 50 34 8 0 1 Yes 28 6 40 44 5 5 1 Yes 32 6 40 27 7 0 0 No 34 6 32 33 2 6 0 No 27 2 40 28 12 3 0 No 28 3 40 33 3 0 0 No 20 9 38 34 1 5 0 No 52 5 40 48 6 0 0 No 26 1 40 21 0 7 0 No 71 5 40 26 3 5 1 Yes 80 2 40 29 16 0 1 Yes 47 7 40 40 4 5 1 Yes 64 3 40 39 2 0 0 No 22 6 40 27 4 0 0 No 36 0 46 39 1 0 1 Yes 24 8 40 27 2 0 0 No 27 2 40 40 4 0 0 No 31 7 40 33 2 0 1 Yes 30 9 40 26 4 0 1 Yes 25 6 40 23 0 8 1 Yes 29 0 48 30 1 0 0 No 34 7 40 53 12 5 0 No 59 5 40 36 12 5 0 No 40 3 45 36 10 0 0 No 45 8 43 64 7 0 1 Yes 98 7 55 43 18 0 1 Yes 56 2 46 28 0 2 0 No 33 0 40 52 3 0 0 No 21 9 30 48 1 7 0 No 31 5 40 43 9 4 0 No 43 4 36 39 16 0 1 Yes 23 4 40 49 4 0 0 No 28 5 45 40 0 5 1 Yes 37 0 36 42 12 0 0 No 30 9 50 28 3 0 0 No 26 7 40 37 10 0 1 Yes 25 4 43 35 1 5 0 No 41 3 35 63 22 0 0 No 92 8 40 50 8 0 1 Yes 41 1 40 49 3 4 0 No 39 7 40 44 5 0 0 No 25 0 37 42 2 0 0 No 45 6 60 36 9 5 1 Yes 32 0 40 42 7 1 0 No 26 7 40 48 9 0 0 No 36 3 40 33 3 8 0 No 25 9 40 35 2 5 0 No 55 4 40 27 5 0 0 No 25 6 42 36 1 0 0 No 33 9 40 39 10 0 1 Yes 40 2 40 61 13 0 0 No 66 4 45 48 4 0 0 No 43 2 41 47 1 0 0 No 22 2 37 30 4 0 0 No 22 4 40 40 17 0 0 No 36 3 42 29 4 3 1 Yes 32 0 40 61 18 3 1 Yes 31 5 40 32 11 6 0 No 53 3 45 58 12 0 0 No 39 5 50 44 10 0 0 No 21 8 40 30 2 0 0 No 32 8 40 55 15 0 0 No 30 2 32 29 3 0 0 No 60 6 40 47 2 0 0 No 42 7 60 42 22 0 1 Yes 21 1 40 38 1 0 0 No 61 9 40 32 6 0 0 No 23 0 40 55 29 5 0 No 29 9 40 43 22 3 0 No 36 8 55 32 11 0 1 Yes 27 7 40 31 10 0 1 Yes 23 0 40 29 3 0 0 No 21 4 40 42 1 1 0 No 24 5 35 38 4 0 1 Yes 44 6 35 37 14 0 1 Yes 24 8 60 47 1 0 0 No 43 7 40 38 10 5 0 No 60 3 35 41 17 0 1 Yes 32 6 45 26 4 0 0 No 37 4 40 31 5 5 0 No 22 8 55 21 2 0 0 No 21 9 40 50 10 0 0 No 100 5 40 36 2 2 1 Yes 40 3 50 41 2 3 0 No 51 5 40 32 5 0 1 Yes 45 0 40 39 5 0 1 Yes 20 5 43 30 0 3 0 No 40 0 45 33 1 0 0 No 28 5 45 27 2 0 0 No 24 6 40 37 15 0 0 No 41 4 65 36 6 0 1 Yes 24 0 40 32 10 0 0 No 45 8 45 31 1 0 1 Yes 40 8 50 45 20 0 1 Yes 65 1 40 44 22 0 0 No 29 0 40 41 0 3 0 No 22 7

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Each Excel project file has two tabs - DATA and Variable INFO. The DATA worksheet contains a YELLOW column representing the numerical response variable and

Each Excel project file has two tabs - DATA and Variable INFO. The DATA worksheet contains a YELLOW column representing the numerical response variable and a DARK ORANGE column representing the numerical predictor variable for this simple regression analysis. Use only these two columns for this part (Part 1) of the project.

Introduction

Assume you are part of the organization or group that uses the data available to you for your team project. Using the YELLOW-highlighted numerical variable column in your Excel worksheet as the response variable of interest, Develop an introductory "scenario" of one paragraph that describes the data file for your project and why you (the ?????? Corporation/Group) are performing this simple regression analysis that will enable you to predict the outcomes of this numerical response variable based on one predictor variable, the DARK ORANGE column.

Background

Using both the response variable (YELLOW column) and the predictor variable (DARK ORANGE column) develop appropriate descriptive summary measures reviewed in Module 1.

Simple Regression Modeling Steps

Open the Excel worksheet containing your Team Project Data.
As you learned in Module 2, run a simple linear regression model using the independent numerical variable whose Excel worksheet column is highlighted in DARK ORANGE as the predictor of Y the YELLOW Excel column.
1. Cut and paste into your report the scatter plot and the Excel Regression Output for this simple linear regression model.
2. Write the sample regression equation.
3. Interpret the meaning of the Y-intercept and slope for your fitted model.
4. Interpret the meaning of the coefficient of determination r ² .
5. Interpret the meaning of the standard error of the estimate SYX .
6. Obtain the residual plots and cut and paste them into the report. Briefly comment on the appropriateness of your fitted model.
  1. (1) If the assumptions are met and the fitted model is appropriate,continue to Step 2G.
  2. (2) If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step 2G. Note -- you do not need to check the assumption of independence in your project. (That assumption is automatically met because your project is not time-dependent).
7. Comment on the statistical significance of your fitted model
8. Comment on the 95% confidence interval estimate on the average impact on the response variable for each unit increase in the predictor variable.
9. Select a value for your independent variable in its relevant range:
  1. Predict

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Each Excel project file has two tabs - DATA and Variable INFO. The DATA worksheet contains a YELLOW column representing the numerical response variable and

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