Set the working directory:

  1. Download “StudentSurvey.csv” to your computer.
  2. Set Working directory to the folder you saved your file in.
  3. read the file using read.csv command.
#If your assignment does not render, you might need to install.packages("htmltools")
library(tidyverse)
## Warning: package 'ggplot2' was built under R version 4.5.2
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   4.0.2     ✔ 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 errors

Instructions:

Read the StudentSurvey into this markdown and answers the following questions

#read the StudentSurvey.csv in here
setwd("~/Desktop/datasets")
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 data structure:

#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
dim(StudentSurvey)
## [1] 79 17
#create a table of students'sex and "HigherSAT"
StudentSurvey[c("Sex", "HigherSAT")]
## # A tibble: 79 × 2
##    Sex   HigherSAT
##    <chr> <chr>    
##  1 M     Math     
##  2 F     Math     
##  3 M     Math     
##  4 M     Math     
##  5 F     Verbal   
##  6 F     Verbal   
##  7 F     Math     
##  8 M     Math     
##  9 F     Math     
## 10 F     Math     
## # ℹ 69 more rows
# 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 <- data.frame(StudentSurvey$Weight, StudentSurvey$Exercise)

column_df
##    StudentSurvey.Weight StudentSurvey.Exercise
## 1                   180                     10
## 2                   120                      4
## 3                   208                     14
## 4                   110                      3
## 5                   150                      3
## 6                   114                      5
## 7                   128                     10
## 8                   235                     13
## 9                   115                     12
## 10                  140                     12
## 11                  135                      6
## 12                  110                     10
## 13                   99                      3
## 14                  165                      7
## 15                  120                      2
## 16                  154                     14
## 17                  110                     10
## 18                  145                     14
## 19                  195                     20
## 20                  200                      7
## 21                  167                     12
## 22                  175                     10
## 23                  155                      6
## 24                  185                     14
## 25                  190                     12
## 26                  165                     10
## 27                  175                      8
## 28                  126                      0
## 29                  187                     10
## 30                  170                      6
## 31                  158                      5
## 32                  119                     24
## 33                  205                      2
## 34                  129                     10
## 35                  145                      6
## 36                  130                      5
## 37                  215                      5
## 38                  135                     12
## 39                  145                      2
## 40                   98                      7
## 41                  150                     15
## 42                  159                      5
## 43                  174                      7
## 44                  160                     15
## 45                  165                      8
## 46                  161                     14
## 47                  130                      4
## 48                  175                     15
## 49                  255                      4
## 50                  160                     15
## 51                  160                      3
## 52                   95                      3
## 53                  115                     15
## 54                  120                     20
## 55                  135                      3
## 56                  180                      6
## 57                  155                     12
## 58                  110                      4
## 59                  215                     20
## 60                  140                     10
## 61                  195                     10
## 62                  185                      4
## 63                  185                      9
## 64                  209                     12
## 65                  145                      2
## 66                  180                      2
## 67                  170                      5
## 68                  135                      5
## 69                  165                      6
## 70                  137                     10
## 71                  147                      4
## 72                  150                      5
## 73                  155                     17
## 74                  160                      7
## 75                  130                      2
## 76                  180                      8
## 77                  150                      1
## 78                  205                     14
## 79                  115                     12
#Access the fourth element in the first column from the StudentSurvey's dataset.

StudentSurvey[4,1]
## # A tibble: 1 × 1
##   Year  
##   <chr> 
## 1 Junior