Homework3
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School
Montgomery College *
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Course
101
Subject
Statistics
Date
Apr 3, 2024
Type
Pages
3
Uploaded by GrandSparrowMaster909
Student Survey
MA
2024-02-05
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.
Instructions:
Read the StudentSurvey into this markdown and answers the following questions
#read the file
my_data <- read.csv("StudentSurvey.csv")
Check the data structure:
#check the head of the data set
head(my_data)
## 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(my_data)
## [1] 79 17
#create a table of students'sex and "HigherSAT"
sex_High_sat<- table(my_data$Sex, my_data$HigherSAT)
sex_High_sat
## ## Math Verbal
## F 25 15
## M 24 15
# Display summary statistics for VerbalSAT
Sat_summary <- summary(my_data$VerbalSAT)
Sat_summary
## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 420.0 550.0 580.0 583.2 630.0 720.0
#Find the average GPA of students
abv_gpa<- mean(my_data$GPA, na.rm = TRUE)
abv_gpa
## [1] 3.169114
#Create a new datafreame "column_df" that contains students' weight and number of hours the exer
cise library
(dplyr)
## ## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## ## filter, lag
## The following objects are masked from 'package:base':
## ## intersect, setdiff, setequal, union
column_df<- select(my_data, Weight, Exercise)
head(column_df)
## Weight Exercise
## 1 180 10
## 2 120 4
## 3 208 14
## 4 110 3
## 5 150 3
## 6 114 5
#access the fourth element in the first column
element <-my_data [4,1 ]
element
## [1] "Junior"
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