Report Write$-$up Structure

Title Page: provides the title of the study along with the names of the team members.

Introduction: is a section introducing the study with a one paragraph scenario that mentions what the study is about and what the objectives are.

Background: is a section describing the numerical dependent $($i$.$e$.,$ response$)$ variable of interest as well as the numerical independent $($predictor$)$ variable that will be used to develop the simple regression model. Appropriate tables, charts, and descriptive summary measures, techniques for which were reviewed in M$1$ should be included in the body of this section or in an Appendix to the report.

Simple Regression Modeling: is a section, based on M$2,$ demonstrating the complete development of a simple linear regression model using an appropriate numerical predictor variable. An appropriate value of the predictor variable should be used to obtain the prediction $($i$.$e$.$ the value of the dependent$/$response variable$),$ along with the confidence interval estimate for the mean response Appropriate tables and charts should be included in the body of this section or in an Appendix to the report.

Summary of Findings: The report should end with a short paragraph that connects to the Introduction section scenario.

Developing the Report

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, create 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 SYX $.$

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 $2$G$.$

$(2)$ If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step $2$G$.$ 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

$$

$5-$Year Return Assets Expense Ratio $1-$Year Return $3-$Year Return CategoryCODE Category$\_$Label

$5\mathrm{.}0158\mathrm{.}20\mathrm{.}617\mathrm{.}66\mathrm{.}31$ Intermediate Govt

$5\mathrm{.}3420\mathrm{.}60\mathrm{.}618\mathrm{.}96\mathrm{.}71$ Intermediate Govt

$5\mathrm{.}0243\mathrm{.}10\mathrm{.}9311\mathrm{.}17\mathrm{.}41$ Intermediate Govt

$5\mathrm{.}424\mathrm{.}70\mathrm{.}497\mathrm{.}36\mathrm{.}51$ Intermediate Govt

$4\mathrm{.}8462\mathrm{.}20\mathrm{.}626\mathrm{.}96\mathrm{.}01$ Intermediate Govt

$5\mathrm{.}9497\mathrm{.}70\mathrm{.}2711\mathrm{.}47\mathrm{.}71$ Intermediate Govt

$5\mathrm{.}04245\mathrm{.}40\mathrm{.}457\mathrm{.}16\mathrm{.}01$ Intermediate Govt

$5\mathrm{.}66337\mathrm{.}80\mathrm{.}4511\mathrm{.}07\mathrm{.}41$ Intermediate Govt

$5\mathrm{.}01609\mathrm{.}60\mathrm{.}4510\mathrm{.}17\mathrm{.}21$ Intermediate Govt

$5\mathrm{.}1414\mathrm{.}30\mathrm{.}507\mathrm{.}76\mathrm{.}11$ Intermediate Govt

$5\mathrm{.}6457\mathrm{.}20\mathrm{.}5512\mathrm{.}47\mathrm{.}61$ Intermediate Govt

$4\mathrm{.}793\mathrm{.}80\mathrm{.}556\mathrm{.}05\mathrm{.}91$ Intermediate Govt

$5\mathrm{.}1152\mathrm{.}50\mathrm{.}728\mathrm{.}46\mathrm{.}31$ Intermediate Govt

$4\mathrm{.}8552\mathrm{.}20\mathrm{.}517\mathrm{.}25\mathrm{.}91$ Intermediate Govt

$5\mathrm{.}214724\mathrm{.}50\mathrm{.}217\mathrm{.}26\mathrm{.}21$ Intermediate Govt

$5\mathrm{.}4217\mathrm{.}20\mathrm{.}6610\mathrm{.}67\mathrm{.}11$ Intermediate Govt

$4\mathrm{.}9491\mathrm{.}61\mathrm{.}0611\mathrm{.}66\mathrm{.}91$ Intermediate Govt

$4\mathrm{.}71255\mathrm{.}00\mathrm{.}497\mathrm{.}15\mathrm{.}81$ Intermediate Govt

$5\mathrm{.}2858\mathrm{.}20\mathrm{.}499\mathrm{.}57\mathrm{.}11$ Intermediate Govt

$4\mathrm{.}7107\mathrm{.}70\mathrm{.}678\mathrm{.}26\mathrm{.}41$ Intermediate Govt

$4\mathrm{.}9120\mathrm{.}20\mathrm{.}658\mathrm{.}36\mathrm{.}21$ Intermediate Govt

$4\mathrm{.}723\mathrm{.}50\mathrm{.}748\mathrm{.}76\mathrm{.}21$ Intermediate Govt

$6\mathrm{.}1303\mathrm{.}20\mathrm{.}3013\mathrm{.}98\mathrm{.}41$ Intermediate Govt

$4\mathrm{.}21100\mathrm{.}40\mathrm{.}238\mathrm{.}45\mathrm{.}91$ Intermediate Govt

$6\mathrm{.}31332\mathrm{.}00\mathrm{.}13$