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/wesle/Downloads/Data 101")
stSu <- read.csv("StudentSurvey.csv")

Check the data structure:

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