A director of research at an acute care hospital observes an increase in the number of patients returning to the hospital within 30 days. The director determines that this is harmful to patients and harmful financially to the hospital. The dataset hospital contains data on a study the director conducted to determine which factors are related to returning to the hospital in 30 days. You can find a description of the variables in the file on pages 40 and 41 in the Auerbach and Zeitlin text.

Using the CrossTables() function in the gmodels package, create a table comparing “return30” and “gender.” Then, use the data in your table to answer the question: Who is more likely to return within 30 days?
Refer to pages 43-45 in the Auerbach & Zeitlin text (Recoding Data) to create a variable: “age80.”
Using the CrossTables() function in the gmodels package, create a table comparing “return30” and “age80.” Then, use the data in your table to answer the question: Who is more likely to return within 30 days?
Copy and paste your tables from RStudio and findings into a Word document. Use 10-point, Courier font.
Upload your findings.
Note: When you use age80 in the CrossTable() function do not use the syntax hospital$age80. Leave off the “hospital$.” You will still need to include hospital$ with return30. The reason for this is that age80 is not part of the hospital data frame.  Refer to pages 46-47 in the Auerbach & Zeitlin text (saving your transformation) to attach your transformation to your data frame.