MGMT 3345 Final R Project

This repository contains the final R analysis project for MGMT 3345, Business Statistics II. The project uses an R Markdown notebook to analyze workplace survey data, with a focus on job satisfaction, workplace rewards, demographic group comparisons, and regression models.

Best Item to Share

The best public-facing link to share is the rendered notebook:

https://sampbaer-creator.github.io/R_Final_Project/

That page is generated from index.html and is the easiest way for someone to review the full analysis without opening RStudio or downloading files.

For a more complete submission package, share these files together:

• index.html - rendered notebook for GitHub Pages
• Final r file.Rmd - R Markdown source code
• MGMT 3345 BIL Final Project.docx - written project report

Project Contents

File	Purpose
Final r file.Rmd	Source R Markdown notebook containing the analysis code and written notes.
Final r file.nb.html	Rendered notebook output created from the R Markdown file.
index.html	Copy of the rendered notebook used as the GitHub Pages landing page.
MGMT 3345 BIL Final Project.docx	Final written project document.
.nojekyll	Allows GitHub Pages to serve the HTML without Jekyll processing.

Analysis Overview

The notebook includes:

• Descriptive statistics for gender, race, ethnicity, education, marital status, Utah residency, and income
• Mean and variance comparisons across gender groups
• Proportion tests for income, education, sales/business development roles, organization tenure, and safe working conditions
• Chi-square tests of independence
• One-way and two-way ANOVA models
• Correlation heat maps for selected job satisfaction predictors
• Linear regression models for job satisfaction by White and non-White respondent groups
• Logistic regression models for employability worry by White and non-White respondent groups

Main R Methods Used

The project demonstrates:

• Frequency tables with tab1
• Two-sample t-tests with t.test
• Variance tests with var.test
• Proportion tests with prop.test
• Chi-square tests with chisq.test
• ANOVA with aov
• Correlation plots with corrplot
• Linear regression with lm
• Logistic regression with glm
• Model table output with broom

Reproducibility Notes

The notebook expects a data frame named BIL to already be loaded in the R environment. The raw dataset and the data-loading step are not included in this repository, so the rendered HTML is the most complete artifact for review.

To rerun the notebook from source, open Final r file.Rmd in RStudio, load the required BIL dataset first, install the required packages, and then knit the notebook.

Likely package dependencies include:

install.packages(c("epiDisplay", "corrplot", "broom", "DescTools"))

Recommended Sharing Approach

For a class submission, share the GitHub Pages link first and include the Word document if the instructor expects the written report.

For a portfolio or resume sample, share the GitHub Pages link and briefly describe the statistical methods used. The rendered notebook is stronger than the repository file list because it shows both the analysis workflow and the results in one place.

For someone who wants to inspect the code, share the repository link:

https://github.com/sampbaer-creator/R_Final_Project