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
 setwd("C:/Users/tonge/Desktop/Data 101")
StudentSurvey_df<- read.csv("StudentSurvey.csv")

Check the data structure:

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