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")

Instructions:

Read the StudentSurvey into this markdown and answers the following questions

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

Check the data structure:

#check the head of the data set
head(StudentData)
##        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(StudentData)
## [1] 79 17
#create a table of students'sex and "HigherSAT"
table(StudentData$Sex, StudentData$HigherSAT)
##    
##     Math Verbal
##   F   25     15
##   M   24     15
# Display summary statistics for VerbalSAT
summary(StudentData$VerbalSAT)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   420.0   550.0   580.0   583.2   630.0   720.0
#Find the average GPA of students
mean(StudentData$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(StudentData$Weight, StudentData$Exercise)
column_df
##    StudentData.Weight StudentData.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.
StudentData[4,1]
## [1] "Junior"