Upload an R script that includes code (with comments and a header) that does the following: 1. Imports the mtcars data. 2. Transform the vs and am variables to factors with labels. 3. Create an...

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Upload an R script that includes code (with comments and a header) that does the following:


1. Imports the mtcars data.


2. Transform the vs and am variables to factors with labels.


3. Create an appropriate graph of the distribution of mpg.


4. Create an appropriate graph of mpg by engine shape.


5. Include R code that creates output that helps determine which of the following groups has the most cars in it within this dataset:



v-shaped engines with automatic transmission, v-shaped engines with manual transmissions, straight engines with automatic transmissions, and straight engines with manual transmissions.




mtcars {datasets}R Documentation Motor Trend Car Road Tests Description The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973–74 models). Usage mtcars Format A data frame with 32 observations on 11 (numeric) variables. [, 1]mpgMiles/(US) gallon [, 2]cylNumber of cylinders [, 3]dispDisplacement (cu.in.) [, 4]hpGross horsepower [, 5]dratRear axle ratio [, 6]wtWeight (1000 lbs) [, 7]qsec1/4 mile time [, 8]vsEngine (0 = V-shaped, 1 = straight) [, 9]amTransmission (0 = automatic, 1 = manual) [,10]gearNumber of forward gears [,11]carbNumber of carburetors Note Henderson and Velleman (1981) comment in a footnote to Table 1: ‘Hocking [original transcriber]'s noncrucial coding of the Mazda's rotary engine as a straight six-cylinder engine and the Porsche's flat engine as a V engine, as well as the inclusion of the diesel Mercedes 240D, have been retained to enable direct comparisons to be made with previous analyses.’ Source Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411. "","mpg","cyl","disp","hp","drat","wt","qsec","vs","am","gear","carb" "Mazda RX4",21,6,160,110,3.9,2.62,16.46,0,1,4,4 "Mazda RX4 Wag",21,6,160,110,3.9,2.875,17.02,0,1,4,4 "Datsun 710",22.8,4,108,93,3.85,2.32,18.61,1,1,4,1 "Hornet 4 Drive",21.4,6,258,110,3.08,3.215,19.44,1,0,3,1 "Hornet Sportabout",18.7,8,360,175,3.15,3.44,17.02,0,0,3,2 "Valiant",18.1,6,225,105,2.76,3.46,20.22,1,0,3,1 "Duster 360",14.3,8,360,245,3.21,3.57,15.84,0,0,3,4 "Merc 240D",24.4,4,146.7,62,3.69,3.19,20,1,0,4,2 "Merc 230",22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2 "Merc 280",19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4 "Merc 280C",17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4 "Merc 450SE",16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3 "Merc 450SL",17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3 "Merc 450SLC",15.2,8,275.8,180,3.07,3.78,18,0,0,3,3 "Cadillac Fleetwood",10.4,8,472,205,2.93,5.25,17.98,0,0,3,4 "Lincoln Continental",10.4,8,460,215,3,5.424,17.82,0,0,3,4 "Chrysler Imperial",14.7,8,440,230,3.23,5.345,17.42,0,0,3,4 "Fiat 128",32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1 "Honda Civic",30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2 "Toyota Corolla",33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1 "Toyota Corona",21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1 "Dodge Challenger",15.5,8,318,150,2.76,3.52,16.87,0,0,3,2 "AMC Javelin",15.2,8,304,150,3.15,3.435,17.3,0,0,3,2 "Camaro Z28",13.3,8,350,245,3.73,3.84,15.41,0,0,3,4 "Pontiac Firebird",19.2,8,400,175,3.08,3.845,17.05,0,0,3,2 "Fiat X1-9",27.3,4,79,66,4.08,1.935,18.9,1,1,4,1 "Porsche 914-2",26,4,120.3,91,4.43,2.14,16.7,0,1,5,2 "Lotus Europa",30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2 "Ford Pantera L",15.8,8,351,264,4.22,3.17,14.5,0,1,5,4 "Ferrari Dino",19.7,6,145,175,3.62,2.77,15.5,0,1,5,6 "Maserati Bora",15,8,301,335,3.54,3.57,14.6,0,1,5,8 "Volvo 142E",21.4,4,121,109,4.11,2.78,18.6,1,1,4,2
Answered Same DayJun 15, 2021

Answer To: Upload an R script that includes code (with comments and a header) that does the following: 1....

Saravana answered on Jun 15 2021
128 Votes
---
title: "mtcars_solution"
output:
html_document:
toc: True
---
```{r setup , echo=FALSE}
# clear all variables
rm(list = ls())
if (!require(ggplot2)) insta
ll.packages('ggplot2')
library(ggplot2)
if (!require(ggstatsplot)) install.packages('ggstatsplot')
library(ggstatsplot)
if (!require(plyr)) install.packages('plyr')
library(plyr)
if (!require(dplyr)) install.packages('dplyr')
library(dplyr)
if (!require(tidyverse)) install.packages('tidyverse')
library(tidyverse)
```
### 1. Imports the mtcars data
```{r ques1}
# set working directory to folder containing the mtcars.csv file
setwd("/media/priyan/Files/GreyNodes/Assignment26")
# search for mtcars.csv file in the working directory
file <-list.files(pattern = "mtcars.csv")
#read the mtcars.csv file using read.table
mtcars <- read.table(file, fill = TRUE,header = TRUE,sep= ",", stringsAsFactors = TRUE)
head(mtcars, 5)
```
### 2. Transform the vs and am variables to factors with labels.
```{r ques2}
# convert vs variable as factor
# vs    Engine (0 = V-shaped, 1 = straight)
mtcars$vs <- as.factor(as.character(mtcars$vs))
# The use revalue() from the plyr package to rename levels of a factor:
# http://www.cookbook-r.com/Manipulating_data/Renaming_levels_of_a_factor/
library(plyr)
mtcars$vs <- revalue(mtcars$vs, c("0"="V_Shaped", "1"="Straight"))
# convert am variable as factor
# Transmission (0 = automatic, 1 = manual)
mtcars$am <- as.factor(as.character(mtcars$am))
# rename levels of factor am
mtcars$am <- revalue(mtcars$am, c("0"="automatic", "1"="manual"))
print("levels of factor vs:")
print(levels(mtcars$vs))
print("levels of factor am:")
print(levels(mtcars$am))
```
### 3. Create an appropriate...
SOLUTION.PDF

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