Reference no: EM13845139

Course Project: Hospital Stays, Impact of Education, Health Data

Introduction

In this case, 40 individuals visited the hospital looking for information and education regarding their diabetes. Since diabetes relates to the body's ability to use glucose, their glucose level was measured. These patience took a knowledge test about diabetes before and after being given some educational materials. Satisfaction with their overall visit was also measured through a survey. The data appear below for your reference. The Excel spreadsheet with these data can be found in Doc Sharing and should be opened in Minitab to complete the analyses required in each part of this project.

The variables are

1. Hospital stay - number of days in hospital

2. Hospital satisfaction - level of satisfaction with hospital services during stay (very highly satisfied, highlysatisfied, somewhat dissatisfied, and very dissatisfied)

3.Diabetes Pretest - score on diabetes knowledge test (must score 95 or higher to leave)

4. Diabetes Posttest - score on diabetes knowledge test after receiving educational material created forthis study

5. Glucose - blood glucose in mg/dL.

The data are available in Doc Sharing Course Project Data Set as an Excel file. You are to copy and pastethe data set into a Minitab Worksheet.

PROJECT PART A: Exploratory Data Analysis

Summarize the data for each of the five variables. For each variable, find the mean, median, variance, and standard deviation. Use Minitab as appropriate, and explain what the results mean. These calculations may not be possible for each variable. If you cannot calculate any or all of these for a specific variable, please note that and state why

Analyze the connections or relationships between two variables. There are ten pairings possible here (Hospital stay and hospital satisfaction, hospital stay and diabetes pretest, hospital stay and diabetes posttest, hospital stay and glucose, hospital satisfaction and diabetes pretest, hospital satisfaction and diabetes posttest, hospital satisfaction and glucose, diabetes pretest and diabetes posttest, diabetes pretest and glucose, and diabetes posttest and glucose ). Choose two of these pairings and find the correlation coefficient and show the scatter plot. Explain what you see. Some variables show clear relationships, while others do not.

Prepare your report in Microsoft Word (or some other word processing package), integrating your graphs and tables with text explanations and interpretations. Be sure that you have graphical and numerical back up for your explanations and interpretations. Be selective in what you include in the report. You should not generate a 20 page report on every variable and every possible relationship. Rather what you should do is to highlight what you see for the individual and two or three sentences of interpretation. For the two pairings you selected, identify and report your results using graphical and numerical summary (as appropriate), with interpretations.

Submission: The report from part 4 including all relevant graphs and numerical analysis along with interpretations.

Format for report:

A. Brief Introduction

B. Discuss your 1st individual variable

C. Discuss your 2nd individual variable

D. Discuss your 3rd individual variable

E. Discuss your 4th individual variable

F. Discuss your 5th individual variable

G. Discuss your 1st pairing of variables

H. Discuss your 2nd pairing of variables

I. Conclusion

Project Part B: Hypothesis Testing and Confidence Intervals

Your manager has speculated the following:

a. The average (mean) level of glucose is less than 130

b. The true population proportion of number somewhat satisfied with their hospital stay is greater than 28%, c. the average (mean) score on the diabetes pretest is greater than 52.

d. The average (mean) score on the diabetes posttest ONLY among those that are "somewhat satisfied" is less than 75.

1. Using the sample data, perform the hypothesis test for each of the above situations in order to see if there is evidence to support your manager's belief in each case a.-d. In each case use the Seven Elements of a Test of Hypothesis, in Section 6.2 of your textbook with α = .05, and explain your conclusion in simple terms. Also be sure to compute the p-value and interpret.

2. Follow this up with computing 95% confidence intervals for Glucose and Diabetes Posttest, and again interpreting these intervals.

3. Write a report to your manager about the results, distilling down the results in a way that would be understandable to someone who does not know statistics. Clear explanations and interpretations are critical.

Project Part C: Regression and Correlation Analysis

Using Minitab perform the regression and correlation analysis for the data on diabetes posttest (Y), the dependent variable, and diabetes pretest (X), the independent variable, by answering the following.

1. Generate a scatterplot for diabetes posttest (Y) vs. diabetes pretest (X) including the graph of the "best fit" line. Interpret.

2. Determine the equation of the "best fit" line, which describes the relationship between diabetes posttest and diabetes pretest.

3. Determine the coefficient of correlation. Interpret.

4. Determine the coefficient of determination. Interpret.

5. Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, including the p-value.

6. Based on your findings in 1-5, what is your opinion about using diabetes pretest to predict diabetes postest? Explain.

7. Compute the 95% confidence interval for beta-1 (the population slope). Interpret this interval. In an attempt to improve the model, we attempt to do a multiple regression model predicting diabetes posttest based on diabetes pretest and glucose.

8. Using Minitab, run the multiple regression analysis using the variables diabetes pretest and glucose to predict diabetes posttest. State the equation for this multiple regression model.

9. Perform the Global Test for Utility (F-Test). Explain your conclusion.

10. Perform the t-test on each independent variable. Explain your conclusions and clearly state how you should proceed. In particular, which independent variables should we keep and which should be discarded. 11. Is this multiple regression model better than the linear model that we generated in parts 1-7? Explain.

Summarize your results from 1-11 in a report that is three pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.