Source: UMUC, 2019
c) Describe the Research Method for Analysis
First, describe the research method in general (e.g., this is a quantitative method and then explain this method in about one paragraph).
Then, explain the statistical method you plan to use for your analysis (Refer to content in Week 3 on Biostatistics for information on various statistical methods you can choose from).
Example:
Hypothesis:  AZ hospitals are more likely to have lower readmission rates for PN compared to CA.
Research Method:  To determine whether Arizona hospitals are more likely to have lower readmission rate than California, we will use a t-test, to determine whether differences across hospital types are statistically significant (You can change the test depends on your analysis).
▪ Add one or two sentences on why you need to see the distribution of data before any analysis (e.g., check for outliers, finding the best-fit test; for example, if the data does not have a normal distribution, you can’t use the parametric test, etc.).
▪ Did you have to eliminate outliers? Indicate what you did.
d) Describe the statistical software package
Add one paragraph for the statistical package, e.g., Excel Analysis ToolPak or RStudio. If you use RStudio, please specify the label or name of the exact R script you used.
5. Results
Discuss your analysis findings considering the following:
▪ Upon analysis, how many observations did you find in your dataset and how many observations did you find for your selected variables, report the % of variable(s) that were missing.
Create tables and other summary tabulations, diagrams, and graphs to present the results of your statistical analysis. You may start with just statistical summaries of your data (summary tables, including N, mean, std. dev.). Then create additional tables to present results that relate directly to your research question(s). Make sure to completely and correctly label all the columns, rows, and titles in any of your tables. Label the tables in sequence (Table 1, Table 2, etc.) so that you can refer to them appropriately in your discussions and other subsequent sections of your analysis report.  Then create appropriate graphs to depict your analysis results. The data in your results tables may be graphed to emphasize a point or relate directly to your research question(s).  Once again, make sure to completely and correctly label all the axes, legends, and titles in any of your graphs. Label the graphs in sequence (Figure 1, Figure 2, etc.) so that you can refer to them appropriately in your discussions and other subsequent sections of your analysis report.  
For example
Table 2. Descriptive analysis to compare % of BL in Medicare beneficiary, MD vs. VA- 2013
VariableObs.MeanSDP-valuePer of Lipid in MD2483.202.320.4064
Per of Lipid in VA     124           82.69
4.41
 

Source: UMUC, 2019
When you have tables and graphs ready, discuss your findings as presented in those tables and graphs and state your statistical conclusion(s).  That is, do the results present evidence in favor of the null hypothesis or evidence that contradicts the null hypothesis?
6. Conclusion and Discussion
Review your research question(s) or hypothesis. 
How has your analysis informed your research question(s) or hypothesis?  Present your conclusion(s) from the results (as presented above) and discuss the meaning of your conclusion(s) considering the research question(s) or hypothesis as presented in your introduction.   
At the end of this section, add one or two sentences to discuss the limitations (including biases) associated with your present analysis and any other statements you think are important in understanding the results of this analysis. 
References
Include a reference page listing the bibliographic information for all sources cited in this report. This information should be consistent with the requirements specified in the American Psychological Association (APA) format and style guide.