Set the working directory:

  1. Download “StudentSurvey.csv” to your computer #done

  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")

Instructions:

Read the StudentSurvey into this markdown and answers the following questions

#set working directory

setwd('/home/raulginomiranda/DATA101 Fall 2025/Week 3/Homework 2')

#read the StudentSurvey.csv in here

s_survey <- read.csv('StudentSurvey.csv')

Check the data structure:

str(s_survey)
## 'data.frame':    79 obs. of  17 variables:
##  $ Year      : chr  "Senior" "Sophomore" "FirstYear" "Junior" ...
##  $ Sex       : chr  "M" "F" "M" "M" ...
##  $ Smoke     : chr  "No" "Yes" "No" "No" ...
##  $ Award     : chr  "Olympic" "Academy" "Nobel" "Nobel" ...
##  $ HigherSAT : chr  "Math" "Math" "Math" "Math" ...
##  $ Exercise  : int  10 4 14 3 3 5 10 13 12 12 ...
##  $ TV        : int  1 7 5 1 3 4 10 8 1 6 ...
##  $ Height    : int  71 66 72 63 65 65 66 74 60 65 ...
##  $ Weight    : int  180 120 208 110 150 114 128 235 115 140 ...
##  $ Siblings  : int  4 2 2 1 1 2 1 1 7 1 ...
##  $ BirthOrder: int  4 2 1 1 1 2 1 1 8 2 ...
##  $ VerbalSAT : int  540 520 550 490 720 600 640 660 670 500 ...
##  $ MathSAT   : int  670 630 560 630 450 550 680 710 700 670 ...
##  $ SAT       : int  1210 1150 1110 1120 1170 1150 1320 1370 1370 1170 ...
##  $ GPA       : num  3.13 2.5 2.55 3.1 2.7 3.2 2.77 3.3 3.7 2.09 ...
##  $ Pulse     : int  54 66 130 78 40 80 94 77 94 63 ...
##  $ Piercings : int  0 3 0 0 6 4 8 0 2 2 ...
#check the head of the data set

head(s_survey)
##        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(s_survey)
## [1] 79 17
#create a table of students'sex and "HigherSAT"

table(s_survey$Sex, s_survey$HigherSAT)
##    
##     Math Verbal
##   F   25     15
##   M   24     15
# Display summary statistics for VerbalSAT
summary(s_survey$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(s_survey$GPA, na.rm= TRUE)
## [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(s_survey[, c('Weight','Exercise')])  #i.e., extract only those 2 columns
column_df   #show it
##    Weight 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.


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