#If your assignment does not render, you might need to install.packages("htmltools")Read the StudentSurvey into this markdown and answers the following questions
#read the StudentSurvey.csv in here
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.2
## ✔ ggplot2 4.0.0 ✔ tibble 3.3.0
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(dplyr)
StudentSurvey <- read_csv ("StudentSurvey.csv")## Rows: 79 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (5): Year, Sex, Smoke, Award, HigherSAT
## dbl (12): Exercise, TV, Height, Weight, Siblings, BirthOrder, VerbalSAT, Mat...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.#check the head of the data set
head(StudentSurvey)## # A tibble: 6 × 17
## Year Sex Smoke Award HigherSAT Exercise TV Height Weight Siblings
## <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Senior M No Olympic Math 10 1 71 180 4
## 2 Sophomore F Yes Academy Math 4 7 66 120 2
## 3 FirstYear M No Nobel Math 14 5 72 208 2
## 4 Junior M No Nobel Math 3 1 63 110 1
## 5 Sophomore F No Nobel Verbal 3 3 65 150 1
## 6 Sophomore F No Nobel Verbal 5 4 65 114 2
## # ℹ 7 more variables: BirthOrder <dbl>, VerbalSAT <dbl>, MathSAT <dbl>,
## # SAT <dbl>, GPA <dbl>, Pulse <dbl>, Piercings <dbl>#check the dimensions
str(StudentSurvey)## spc_tbl_ [79 × 17] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Year : chr [1:79] "Senior" "Sophomore" "FirstYear" "Junior" ...
## $ Sex : chr [1:79] "M" "F" "M" "M" ...
## $ Smoke : chr [1:79] "No" "Yes" "No" "No" ...
## $ Award : chr [1:79] "Olympic" "Academy" "Nobel" "Nobel" ...
## $ HigherSAT : chr [1:79] "Math" "Math" "Math" "Math" ...
## $ Exercise : num [1:79] 10 4 14 3 3 5 10 13 12 12 ...
## $ TV : num [1:79] 1 7 5 1 3 4 10 8 1 6 ...
## $ Height : num [1:79] 71 66 72 63 65 65 66 74 60 65 ...
## $ Weight : num [1:79] 180 120 208 110 150 114 128 235 115 140 ...
## $ Siblings : num [1:79] 4 2 2 1 1 2 1 1 7 1 ...
## $ BirthOrder: num [1:79] 4 2 1 1 1 2 1 1 8 2 ...
## $ VerbalSAT : num [1:79] 540 520 550 490 720 600 640 660 670 500 ...
## $ MathSAT : num [1:79] 670 630 560 630 450 550 680 710 700 670 ...
## $ SAT : num [1:79] 1210 1150 1110 1120 1170 1150 1320 1370 1370 1170 ...
## $ GPA : num [1:79] 3.13 2.5 2.55 3.1 2.7 3.2 2.77 3.3 3.7 2.09 ...
## $ Pulse : num [1:79] 54 66 130 78 40 80 94 77 94 63 ...
## $ Piercings : num [1:79] 0 3 0 0 6 4 8 0 2 2 ...
## - attr(*, "spec")=
## .. cols(
## .. Year = col_character(),
## .. Sex = col_character(),
## .. Smoke = col_character(),
## .. Award = col_character(),
## .. HigherSAT = col_character(),
## .. Exercise = col_double(),
## .. TV = col_double(),
## .. Height = col_double(),
## .. Weight = col_double(),
## .. Siblings = col_double(),
## .. BirthOrder = col_double(),
## .. VerbalSAT = col_double(),
## .. MathSAT = col_double(),
## .. SAT = col_double(),
## .. GPA = col_double(),
## .. Pulse = col_double(),
## .. Piercings = col_double()
## .. )
## - attr(*, "problems")=<externalptr>#create a table of students'sex and "HigherSAT"
table(StudentSurvey$Sex, StudentSurvey$HigherSAT)##
## Math Verbal
## F 25 15
## M 24 15# Display summary statistics for VerbalSAT
summary(StudentSurvey$VerbalSAT)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 420.0 550.0 580.0 583.2 630.0 720.0#Find the average GPA of students
mean(StudentSurvey$GPA)## [1] 3.169114#Create a new dataframe, call it "column_df". This new dataframe should contain students' weight and number of hours the exercise
column_df <- StudentSurvey[c("Weight", "Exercise")]
head(column_df)## # A tibble: 6 × 2
## Weight Exercise
## <dbl> <dbl>
## 1 180 10
## 2 120 4
## 3 208 14
## 4 110 3
## 5 150 3
## 6 114 5#Access the fourth element in the first column from the StudentSurvey's dataset.
StudentSurvey[4,1]## # A tibble: 1 × 1
## Year
## <chr>
## 1 Junior