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Overview Data measurement is an important aspect of data analytics. Identifying
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Data measurement is an important aspect of data analytics. Identifying trends in key attributes of data is a fundamental measurement for various aspects in business data and an important skill for business professionals.
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:
Option A: Open a small facility of 90–100 beds.
Option B: Open a medium-sized facility of 300–350 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.
Your work here in Phase One is to do a current trend analysis, which will help you test your initial hypothesis as to which size facility is most profitable. You will use the work here as a foundation for Phase Two (in Milestone Two).
For this assignment, you will analyze the data from the Hospital Data Set and identify trends and patterns in the current operations. You will submit a written current state analysis report. You will also create multiple charts to present the descriiptive analysis you performed. To organize this information, you will create and submit a Data Analysis Workbook in Excel. For this milestone, you will add three sheets to the workbook, and you’ll add more as you complete your Milestone Two assignment.
Specifically, you must address the following rubric criteria:
Descriiptive Statistics: Create an Excel file and title it Data Analysis Workbook. Within your workbook, create a sheet titled P1_Descriiptive Analysis. Present descriiptive 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 descriiptive analysis.
Analysis: Form and explain your initial hypothesis based on your analysis of the charts and trends in Excel.
Which option (Option A or Option B) would you choose at this point in 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.