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GP.F: Univariate Graphs (10 points) InstructionsIf you need a reminder about graphing one variable at a time in R, watch this video. There are a variety of conventional ways to visualize data—tables,...

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GP.F: Univariate Graphs (10 points)
InstructionsIf you need a reminder about graphing one variable at a time in R, watch this video.
There are a variety of conventional ways to visualize data—tables, histograms, bar graphs, etc.
Now that your data have been managed, it is time to graph your variables one at a time and examine both center and spread. Include univariate graphs of your two main constructs.These main constructs, or variables, should be managed (from GP.D).
• Each graph should contain clearly labeled x-axes, y-axes, and legends, if applicable. Write a few sentences describing what your graphs reveal in terms of shape, spread, and center (if variable is quantitative) and most/least frequent categories if variable is categorical.
Submit your assignment as a PDF document on Canvas.

Answered Same Day Nov 04, 2021

Solution

Subhanbasha answered on Nov 07 2021
141 Votes
---
title: "Univariate Graphs"
output: pdf_document
---
```{r message=FALSE, warning=FALSE}
# Installing Required packages
# install.packages("ggplot2")
# install.packages("DescTools")
# Loading required packages
li
ary( DescTools)
li
ary(ggplot2)
# reading a data
Covid <- read.csv("covid data.csv", header = TRUE)
```
```{r}
# checking structure of the data
str(Covid)
# selecting some of the rows
Covid_data <- subset(Covid,select = c("PHYS1A", "PHYS1B", "PHYS1C", "PHYS1D", "PHYS1F"))
```
```{r}
# changing the data into numerical
Covid_data$Fever <- ifelse(Covid_data$PHYS1A=="(2) No",2,ifelse(Covid_data$PHYS1A=="(1) Yes",1,ifelse(Covid_data$PHYS1A=="(77) Not sure",77,98)))
Covid_data$Chills <- ifelse(Covid_data$PHYS1B=="(2) No",2,ifelse(Covid_data$PHYS1B=="(1) Yes",1,ifelse(Covid_data$PHYS1B=="(77) Not sure",77,98)))
Covid_data$Runny_Nose <- ifelse(Covid_data$PHYS1C=="(2) No",2,ifelse(Covid_data$PHYS1C=="(1) Yes",1,ifelse(Covid_data$PHYS1C=="(77) Not sure",77,98)))
Covid_data$Congestion <- ifelse(Covid_data$PHYS1D=="(2) No",2,ifelse(Covid_data$PHYS1D=="(1) Yes",1,ifelse(Covid_data$PHYS1D=="(77) Not sure",77,98)))
Covid_data$Cough <-...
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