Linear Regression Model on Microsoft Excel and R-Studio Linear Regression Model Exercise 4 offers two versions: EXCEL (base) and RStudio (BONUS) Track 1 RStudio: If you have chosen to work with RStudio (1 % BONUS), please run the following models and complete the following tables. See Track 2 below for EXCEL 1st Model:

QUESTION

Linear Regression Model

Exercise 4 offers two versions: EXCEL (base) and RStudio (BONUS)

Track 1 RStudio: If you have chosen to work with RStudio (1 % BONUS), please run the following models and complete the following tables. See Track 2 below for EXCEL

1st Model:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital’s ownership on hospital net-benefit? Discuss your finding, do you think having higher beds has positive impact on the hospital net benefit? What about the ownership?

2nd Model:

Now, estimate the impact of being a member of a system on hospital net benefit. And discuss your finding (nor more than 2 lines). Is the result significant? Explain.

3rd Model:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in your model. How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital revenues?

Based on your finding please recommend 3 policies to improve hospital performance. Please make sure to use the final model for your recommendation.

Discuss your findings. Make sure to attach the plotted information

Track 2 EXCEL: If you have chosen to work with Excel, please run above three models and complete the following tables.

Model 1:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital net-benefit in teaching hospitals.

Model 2:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital net-benefit in non-teaching hospitals.

Use the results from model 1 and model 2 and compare the results between teaching and non-teaching hospitals.

Model 3:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in the first model. How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital net-benefit in teaching hospitals?

Model 4:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in the first model. How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital net-benefit in non-teaching hospitals?

Based on your finding please recommend 3 policies to improve hospital performance. Please make sure to use the final model for your recommendation.

ANSWER

For the RStudio track, you are asked to run three linear regression models and discuss the findings. Here are the details for each model:

1st Model

In this model, you need to predict the difference between hospital beds (bed-tot) and hospital net benefit using ownership as a predictor. You should run a linear regression model and examine the coefficients and standard errors for hospital beds and ownership variables. Calculate the R-squared value to assess the model’s goodness of fit.

2nd Model

For the second model, you are required to estimate the impact of being a member of a system on hospital net benefit. Run a linear regression model, including hospital beds, ownership, and membership variables. Discuss the significance of the results and provide a brief explanation.

3rd Model

In the third model, add the variables ratio-Medicare-discharge and ratio-Medicaid-discharge to the previous model. Assess the impact of having higher Medicare and Medicaid patients on hospital revenues. Again, examine the coefficients and standard errors, and calculate the R-squared value.

Based on the findings from the final model, you need to recommend three policies to improve hospital performance. Ensure that you use the final model for these recommendations.

As for the Excel track, you are asked to run four models and complete the corresponding tables. Here’s a breakdown of the models:

Model 1

Run a linear regression model to predict the difference between hospital beds (bed-tot) and hospital net benefit in teaching hospitals. Calculate the coefficients, standard errors, t-statistics, p-values, and confidence intervals. Also, calculate the R-squared value.

Model 2

Repeat the process for non-teaching hospitals and compare the results with Model 1.

Model 3

Include the variables ratio-Medicare-discharge and ratio-Medicaid-discharge in the first model and assess their impact on hospital net benefit in teaching hospitals. Calculate the coefficients, standard errors, t-statistics, p-values, confidence intervals, and R-squared value.

Model 4

Repeat the process for non-teaching hospitals and analyze the impact of Medicare and Medicaid patients on hospital net benefit.

After analyzing the findings from the final model, you should recommend three policies to improve hospital performance.

Since you requested an essay format optimizing SEO, I can provide you with a general structure for your essay:

Introduction

   – Briefly explain the importance of hospital performance and the relevance of the chosen models.

   – Provide an overview of the variables and models used.

Model Analysis

   – For each model, present the coefficients, standard errors, and statistical significance of the variables.

   – Interpret the findings, focusing on the variables of interest (e.g., hospital beds, ownership, membership, Medicare/Medicaid ratios).

   – Discuss the impact of these variables on hospital net benefit, considering their coefficients and statistical significance.

   – Calculate and interpret the R-squared values to assess the goodness of fit for each model.

Comparison (Excel Track)

   – Compare the results between teaching and non-teaching hospitals based on Model 1 and Model 2.

   – Analyze the differences in the coefficients and their implications for hospital net benefit.

Policy Recommendations

   – Based on the final model’s findings, propose three policies to improve hospital performance.

   – Each policy should be supported by the results and interpretations from the regression analysis.

   – Discuss the potential benefits and implementation strategies for each policy.

Conclusion

   – Summarize the key findings from the regression models and their implications for hospital performance

 Emphasize the policy recommendations and their potential to drive positive change.

   – Conclude by highlighting the importance of data-driven decision-making in healthcare.

Remember to include any necessary plots or visualizations to support your analysis. Good luck with your project!