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")
#Look at Titanic Data Frame Activity for reference

Instructions:

Read the StudentSurvey into this markdown and answers the following questions

#read the StudentSurvey.csv in here
setwd("~/Documents/RStudio (DATA-101)")
Student <- read.csv("StudentSurvey.csv")

Check the data structure:

str(Student)
## '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 dimensions
dim(Student)
## [1] 79 17
#create a table of students'sex and "HigherSAT"

table(Student$Sex, Student$HigherSAT)
##    
##     Math Verbal
##   F   25     15
##   M   24     15
# Display summary statistics for VerbalSAT

summary(Student$VerbalSAT)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   420.0   550.0   580.0   583.2   630.0   720.0
#Find the average GPA of students
(mean(Student$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(Student$Weight, Student$Exercise)
column_df
##    Student.Weight Student.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.
 Student[4,1] #Row 1st then Column 2nd
## [1] "Junior"