Hospital Chain Data Analysis and Recommendations

Part 1: Data Analysis Workbook

Competencies In this project, you will demonstrate your mastery of the following competencies: Use descriptive statistics for business analysis Perform regression analysis to address an authentic problem Apply statistics in the business environment Overview You have been hired as a consultant by a large hospital chain. As part of its expansion plan, the organization wants to open a new hospital in a small- to medium-sized town (with a population of 10,000–50,000). Previously, senior management hired a market research firm to do an initial feasibility analysis. The firm presented the management team with two options: Open a small facility of 900–1,000 beds. Open a medium-sized facility of 3,000–4,000 beds. The hospital’s vice president of operations and finance has tasked you with doing an in-depth analysis to determine which of the two options will be the most profitable, given the expense range of $55–$75 million. The hospital has provided you with a data set that contains data about admissions, personnel, and hospital beds, and attributes of the data such as outpatient visits, births, total expense, and census information. Prompt Part 1: Data Analysis Workbook Analyze the data from the provided Hospital Data Set (linked below) and identify current and future trends and patterns in operations. Descriptive Analysis: Open a new Excel file and title it Data Analysis Workbook. In the workbook, create a sheet titled P1_Descriptive Analysis. Present descriptive statistics (mean, median, standard deviation, and range) in a table for four attributes from the data set. Analyze the current hospital data to identify trends and patterns in hospital admissions and costs. Admission Trends and Charts: Create a sheet titled P1_Admission Trends in your Data Analysis Workbook. Then, create two pie charts and two column/bar charts. For Pie Chart #1: One slice should be labeled Admissions. Choose another attribute for the second slice. For Pie Chart #2, both slices can be attributes of your choice. For the two column/bar charts: Ensure that one column is titled Admissions for both charts. Choose a different attribute for the other column. Expense Trends and Charts: Create a sheet titled P1_Expense Trends in your Data Analysis Workbook. Then, create two column charts and two line charts. For the two column/bar charts: Ensure that one column is titled Expense for both charts. Choose a different attribute for the other column. For Line Chart #1, one of the lines should represent Expense; choose another attribute for the second line. For Line Chart #2, both lines can represent attributes of your choice. Outliers: Identify any outliers that you see and explain how they have an impact on the overall admission and expense trends. Outliers are the data points that can have an impact on your averages and basic descriptive analysis. Identify future trends and attributes that impact expenses and admissions by adding new sheets to your Data Analysis Workbook per the descriptions below. Perform two bivariate regressions to provide recommendations. For the first bivariate regression, the dependent variable should be Total Expense. Choose an independent variable from one of the remaining attributes. Create a sheet titled P2_1st_Bivariate_Regression in your Data Analysis Workbook. For the second bivariate regression, the dependent variable should be Admissions. Choose an independent variable from one of the remaining variables. Create a sheet titled P2_2nd_Bivariate_Regression in your Data Analysis Workbook. What would be the right attribute size (independent variable) seems most appropriate to lead you in the expense range of $55–$75 million? Perform two multivariate regressions to provide recommendations. For the first multivariate regression, the dependent variable should be Total Expense (the column in the data set). Choose two independent variables from one of the remaining attributes. Within your Data Analysis Workbook, create a sheet titled P2_1st_Multi_Regression. Which combination of the attributes seems most appropriate to lead you in the expense range of $55–$75 million? For the second multivariate regression, the dependent variable should be Admissions (the column name in the data set). You should choose two independent variables from one of the remaining attributes. Within your Data Analysis Workbook, create a sheet titled P2_2nd_Multi_Regression. Which combination of the attributes would seem appropriate that would lead you in the expense range of $55–$75 million? Part 2: Final Recommendation Analysis PowerPoint Presentation Create a presentation designed for senior management and the board of directors to share the results of your analysis and provide your final recommendation. Current State Analysis (slides 1–3): State the option (A or B) that you chose and three reasons for your choice. Which option (Option A or Option B) would you choose based on your analysis, given the expense range of $55–$75 million? Why did you choose your selected attributes? Describe any relationships or trends you observed while conducting your analysis. Predictions and Trends Analysis (slides 4–6): Present the predictions based on the regressions that you have analyzed. Briefly describe the key elements for each regression presented in Excel. Cite the regression coefficient, regression line equation, p–value, and significance F in your description. Which of the independent variables are impactful, and why? Summary (slide 7): Summarize your findings for an executive audience. Guidelines for Submission To complete this project, you must submit the following: Data Analysis Workbook Submit your Data Analysis Workbook as an Excel file. Final Recommendations Analysis: Create a PowerPoint presentation with 7-10 slides. Any sources should be cited according to APA style. Consult the Shapiro Library APA Style Guide for more information on citations. Supporting Materials The following resources support your work on the project: Data Set: Hospital Data Set Use the following two sheets: All Hospitals Small Hospitals (Beds <= 40)