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.

install.packages(“htmltools”)

#If your assignment does not render, you might need to install.packages("htmltools")

Instructions:

Read the StudentSurvey into this markdown and answers the following questions

#Setting Working directory
setwd("C:/Users/Joanne G/OneDrive/Data101(Fall 2025)/Datasets")

#read the StudentSurvey.csv in here
df <- read.csv("StudentSurvey.csv")

Check the data structure:

#check the head of the data set
head(df)
##        Year Sex Smoke   Award HigherSAT Exercise TV Height Weight Siblings
## 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
##   BirthOrder VerbalSAT MathSAT  SAT  GPA Pulse Piercings
## 1          4       540     670 1210 3.13    54         0
## 2          2       520     630 1150 2.50    66         3
## 3          1       550     560 1110 2.55   130         0
## 4          1       490     630 1120 3.10    78         0
## 5          1       720     450 1170 2.70    40         6
## 6          2       600     550 1150 3.20    80         4
#check the dimensions
dim(df)
## [1] 79 17
#create a table of students'sex and "HigherSAT"
table(df$Sex,df$HigherSAT)
##    
##     Math Verbal
##   F   25     15
##   M   24     15
# Display summary statistics for VerbalSAT
summary(df$VerbalSAT)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   420.0   550.0   580.0   583.2   630.0   720.0
#Find the average GPA of students
mean(df$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(df$Weight,df$Exercise)
column_df
##    df.Weight df.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.

df[4,1]
## [1] "Junior"