A normally distributed population has mean 57.7 and standard deviation 12.1Find the probability that the mean of a sample of size 16 drawn from this population is less than 45

University of Maryland University College HMGT 400 Research and Data Analysis in Health- FINAL EXAM Dataset: HMGTFINALEXAM.csv (To be provided when you complete Assignment #3) Required program: EXCEL Author, Hossein Zare, PhD Citation: Zare, H. (2019). HMGT 400 Research and Data Analysis in Health Care. FINAL EXAM. UMUC.EDU Question #1 (15 credits): The FINAL EXAM dataset provides some information about hospitals in 2011 and 2012. Analyze the FINAL EXAM dataset. You may calculate the “Hospital Beds per Population (Per Capita)” variable by dividing “total_hospital_beds by tot_population. Use the analysis results to complete Table 1 below. Table 1. Descriptive statistics about hospitals in 2011 & 2012 2011 2012 t Value (Pr<|t|) N Mean St. Dev N Mean St. Dev Hospital Characteristics 1. Hospital beds 2. Number of paid Employee 3. Number of non-paid Employee 4. Internes and Residents 5. System Membership 6. Total hospital cost 7. Total hospital revenues 8. Hospital net benefit 9. Available Medicare days 10. Available Medicaid days 11. Total Hospital Discharge 12. Medicare discharge 13. Medicaid discharge Socio-Economic Variables 14. Hospital Beds per Population (Per Capita) 15. Percent of population in poverty 16. Percent of Female population in poverty 17.Percent of Male population in poverty 18. Median Household Income Then please answer the following questions. What are the significant differences for each of the hospital characteristics between 2011 and 2012?What are the significant differences for each of the socio-economic variables between 2011 and 2012?Based on your findings did hospitals (in general) have a better performance in 2011 or 2012? Explain.How does hospital performance relate to the hospital characteristics and how does it relate to the socio-economic characteristics? Question #2 (15 credits): In the dataset, create a new variable called hospital net benefits. Do this by subtracting hospital costs from hospital revenues. Analyze the dataset and then complete Table 2. In the last column report the T-test results, to compare hospital characteristics and the nationwide socioeconomic variables for for-profit and non-profit hospitals. Table 2. Descriptive statistics between teaching and non-teaching hospitals, 2011 & 2012 For Profit Non-For-Profit p-value N Mean St. Dev N Mean St. Dev Hospital Characteristics 1. Hospital beds 2. Number of paid Employee 3. Number of non-paid Employee 4. Internes and Residents 5. System Membership 6. Total hospital cost 7. Total hospital revenues 8. Hospital net benefit 9. Available Medicare days 10. Available Medicaid days 11. Total Hospital Discharge 12. Medicare discharge 13. Medicaid discharge Socio-Economic Variables 14. Hospital Beds per Population (Per Capita) 15. Percent of population in poverty 16. Percent of Female population in poverty 17. Percent of Male population in poverty 18. Median Household Income Then answer the following questions: What are the main significant differences between for-profit and non-profit hospitals? Which test is the best fit test? Why?Use a box-plot and compare Hospital net benefit between for-profit and non-profit hospitals.Create a scatter plot with the correct variable and axes labels and legend. Use the plot to compare hospital cost (x-axes) and revenue (y-axes) and discuss your findings?If we assume that hospital net-benefit is a good measure of hospital performance, which type of hospitals had the better performance (for-profit or non-profit hospitals)?Overall, what are the main statistically significant differences between for-profit and non-for-profit hospitals? Question #3 (15 credits): The dataset provides the variable herf_ins called the Herfindahl–Hirschman Index which measures market concentration for the health insurance market. Please note that unlike the class exercise in which you used herf_cat, which measured market concentration for the hospital market, in this assignment you are using herf_ins which measures market concentration for the health insurance market. Analyze the data to complete Table 3 (below): Table 3. Comparing hospital characteristics and market, 2011 and 2012 High Competitive Market Moderate Competitive Market Low Competitive Market ANOVA/Chi-Sq (results) N Mean STD N Mean STD N Mean STD Hospital Characteristics 1. Hospital beds 2. Number of paid Employee 3. Number of non-paid Employee 4. Internes and Residents 5. System Membership 6. Total hospital cost 7. Total hospital revenues 8. Hospital net benefit 9. Available Medicare days 10. Available Medicaid days 11. Total Hospital Discharge 12. Medicare discharge-ratio 13. Medicaid discharge-ratio Socio-Economic Variables 14. Hospital Beds per Population (Per Capita) 15. Median Household Income Then answer the following questions: In a short paragraph describe and explain what the Herfindahl index is. You can use the reference provided in the class exercise or any other citation.Compare the following information between hospitals located in high, moderate and low competitive health insurance markets? What are the main significant differences between hospitals in different insurance markets? (use the ANOVA test)What is the impact of being in a high-competitive health insurance market on hospital revenues and costs? Does being in a high-competitive market have a positive impact on net hospital benefits?What about the number of Medicare and Medicaid discharges? Are hospitals in high competitive insurance markets more likely to accept Medicare and Medicaid patients? What is the impact of other variables? (Note: to answer the last question, please compute Medicare-discharge ratios and Medicaid-discharge ratios first and then run two t-Tests (high competitive vs. moderate competitive, and high vs. low competitive market). Please support your findings with a box-plot). Question #4 (Credits 20)- Excel version If you have chosen to work with Excel, please run the models and complete the following tables. Regression Model 1: Analyze the data by running a linear regression model as depicted in Table 4 below. Table 4 – Regression Model 1 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hospital Dummy N = R Square = Describe and discuss your findings. Do the number of hospital beds or whether a hospital is a teaching hospital or not have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance. Regression Model 2: Analyze the data by running a linear regression model as depicted in Table 5 below. Table 5 – Regression Model 2 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hospital Dummy N = R Square = Describe and discuss your findings. Do the number of hospital beds or whether a hospital is a non-teaching hospital or not have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance.Use the results from your Regression model 1 and regression model 2 to comment on any differences or similarities in impact of teaching hospital status or non-teaching hospital status impacts on hospital net-benefit. (hospital performance)? Regression Model 3: Analyze the data by running a linear regression model as depicted in Table 5 below. Table 6 – Regression Model 3 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio N = R Square = Describe and discuss your findings. Do the number of Medicare or Medicaid patients in a teaching hospital have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance. Regression Model 4: Analyze the data by running a linear regression model as depicted in Table 7 below. Table 7 – Regression Model 4 Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Non-Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio N = R Square = Describe and discuss your findings. Do the number of Medicare or Medicaid patients in a non-teaching hospital have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance.Based on your findings please recommend three policies to improve hospital performance. Please make sure to use the final model for your recommendation Question #5 (Credits 20)- Excel version If you have chosen to work with Excel, please run three models and complete the following tables. Logistic Regression Models If you have chosen to work with RStudio, please run the following model and complete the following tables. Logistic Model 1: Analyze the data by running a logistic regression model as depicted in Table 8 below. Use “being a member of a hospital network” (system_member) as the dependent variable. Table 8 – Logistic Model 1 Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital costs N = R Square = Describe and discuss your findings. Logistic Model 2: Analyze the data by running a logistic regression model as depicted in Table 9 below. Table 9 – Logistic Model 2 Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital Costs Total Hospital Revenue N = R Square = Describe and discuss your findings. Logistic Model 3: Analyze the data by running a logistic regression model as depicted in Table 10 below. Table 10 – Logistic Regression Model 3 Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital Costs Total Hospital Revenue Medicare discharge ratio Medicaid discharge ratio N = R Square = Describe and discuss your findings. What is the impact of having more Medicare or more Medicaid patients in the hospitals, on membership in hospital systems? Based on your findings from Logistic Regression Model 3, please recommend three policies to justify whether hospitals will organize themselves into hospital systems or not. Question 6 (15 credits) 1. Please offer a research question for the study using human subject research. 2. Explain the difference between the research process involving human subjects and the research process not involving human subjects. 3. Discuss ethical implications surrounding human subject research studies. 4. Explain the governance of the human subject research studies over the data and the process. 5. Provide examples of the consequences for not meeting IRB (Institutional Review Board) protocol requirements.