Chat with us, powered by LiveChat HMGT 400 Research and Data Analysis in Health Care-Exercise. UMGC.EDU Exercise # 1 Instructions: 1. You may download the datase | WriteDen

## 13 Jan HMGT 400 Research and Data Analysis in Health Care-Exercise. UMGC.EDU Exercise # 1 Instructions: 1. You may download the datase

ASSIGNMENTS & ETC ATTACHED

Required analysis program: Analysis ToolPak – for all analyses in this class (RStudio or R Programming for BONUS point seekers only – 10 bonus points if used for analysis).

Author, Hossein Zare, PhD

Citation: Zare, H. (2017). HMGT 400 Research and Data Analysis in Health Care-Exercise. UMGC.EDU

Exercise # 1 Instructions:

1. You may download the dataset from the link below. This dataset provides information about hospitals in 2011 and 2012. Before you do that however consult the additional instructions that I provided to you in 4 PDF email attachments.  ([a]. Ex 1 – Additional Instructions [b] Ex 1 – Instructions t-Test to compare means [c] Ex 1 – Example t-Test Output. [d] Ex 1 – Example Output – Graphs).

2. Analyze the data, using these instructions. Your objective is to use the results of your analysis to create "summary statistics" (Count (N), Mean, and Standard Deviation) for each hospital characteristic and each year (2011 and 2012) and complete Table 1 (template below). You should then create any meaningful graphs (using Excel) to summarize your findings and to write a short paragraph summary report describing your findings.

3. Your report may be in WORD format, with the tables you create in Excel copied and pasted in WORD. Submit your report to the appropriate folder.

Table 1. Descriptive statistics between hospitals in 2011 & 2012

Exercise 1 Findings: Based on your findings, in which years did the hospitals have better performance? Please write a short paragraph and describe your findings. Make sure to attach plot(s) or graph(s) of the information to your report.

Instructions:

Use Analysis ToolPak for all analyses (mandatory).

(for BONUS points: Use RStudio. The R script is available below for this exercise, but you need to modify the script for this analysis).

Download RStudio script from here (If you were not able to load the DPLYR package use this scrip):E1-Codes-No-Dplyr

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