Directions
1. Load the assignment data into R studio with read.csv. Assign the loaded data to a variable.
2. Use factor() to create factor variables for all the variables in the study. E.g. agef = factor(d$Age), where d is the variable that was assigned to the loaded csv data.
3. Create a table() for each of the variables in the survey.
4. Generate a frequency table showing the absolute frequencies for both Gender and Care Transition in one table. You should have the Gender as the table columns (i.e. listed second).
5. Generate a table showing the proportions for Gender and Care Transition in one table. You should have the Gender as the table columns (i.e. listed second).
6. Install the package tidyverse and make a call to the library ggplot2
install.packages(“tidyverse”,dependencies=TRUE)
library(ggplot2)
7. Using ggplot, make a barplot showing the frequencies for care transition.
8. Conduct a prop.test() to determine if survey respondents are more likely to be boys than girls.
9. Save your R code, results, and graphs in one report.
Data Analysis: Use your results to complete the following sentences.
1. In this data set there is data for ______ participants. There were ______ males and ______ females who completed the survey.
2. There were ______ patients who were somewhat dissatisfied with care transition.
3. There were ______ females who were very satisfied and ______ males who were very satisfied.
4. There were ______ females who were very dissatisfied and ______ males who were very dissatisfied.
5. Discuss the results of the prop.test to determine if survey respondents are more likely to be boys than girls.
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