R-Assignment 1 (Kevin Pham)

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Montgomery College *

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100

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Statistics

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Feb 20, 2024

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Kevin Pham STAT100 Section 0331 R-Assignment 1 Question 1. - total number of Joe's beverages from Dunkin .b. - total number of mechanical pencils Nora has after giving away 7 1 1l.c. - average number of credits Bella has to take in her first two years 4 + 16 + 15 + 16) / 4 VeV V'I:IV VeV Vv # 1.d. - calculate 546 > 5A6 [1] 15625 > Question 2. # 2.a. - create four variables for Joe's beverages from Dunkin # number of iced coffees iced_coffee <- § # number of iced Tattes iced_Tatte <- 2 # number of hot coffees hot_coffee <- 4 # total number of beverages using the variables created total_beverages <- iced_coffee + iced_latte + hot_coffee total_beverages 1] 11 # 2.b. - create three variables for Nora's pencils # total number of pencils in the pack total_pencils_in_pack <- 20 # number of pencils Kelly receives pencils_kelly_receives <- 7 # nuumber of pencils that Nora ends up with total_pencils_in_pack - pencils_kelly_receives 13 PV VVVVVVMAVYVYYVYYVYVYVYVYVYVV = [ 2.c. - create three variables <_ Ilupll <- "Teft" <- "right" up "left" = —HOWN I E OW S H = "right" VI_IVl_IV'l:IVVVVV Question 3.

> # 3.a. - creating vectors > bella_number_of_credits <- c¢(14, 16, 18, 18) > class(bella_number_of_credits) [1] "numeric" > bella_number_of_credits [1] 14 16 18 18 > # 3.b. - number of credits for Evelyn using vectors > evelyn_number_of_credits <- c(12, 16, 18, 18) > class(evelyn_number_of_credits) [1] "numeric" > evelyn_number_of_credits [1] 12 16 18 18 > # 3.c. - names of four semesters using vectors > semester_term <- c("Fall 2019", "Spring 2020", "Fall 2020", "Spring 2021") > summary(semester_term) Length Class Mode 4 character character > names(bella_number_of_credits) <- c(semester_term) > bella_number_of_credits Fall 2019 Spring 2020 Fall 2020 Spring 2021 14 16 18 18 > names(evelyn_number_of_credits) <- c(semester_term) evelyn_number_of_credits Fall 2019 Spring 2020 Fall 2020 Spring 2021 12 16 18 18 Vv > > > bella_average_credits <-mean(bella_number_of_credits) > bella_average_credits [1] 16.5 > evelyn_average_credits <-mean(evelyn_number_of_credits) > evelyn_average_credits [1] 16 > Question 4. > # 4.a. - create a data frame with variables and vectors > student_id <- ¢(2025001, 2025002, 2025003, 2025004, 2025005, 2025006, 2025007, 202 5008, 2025009, 2025010) > student_gender <- c("Female", "Male", "Female", "Male", "Male", "Other", "Female", "Prefer Not to Say", "Male", "Female") > course_credits <- c(16, 14, 12, 16, 10, 15, 16, 12, 14, 15) > hs_gpa <- ¢(3.85, 3.35, 3.70, 3.25, 3.60, 4.10, 3.95, 3.15, 3.50, 3.45) > student_id [1] 2025001 2025002 2025003 2025004 2025005 2025006 2025007 2025008 2025009 [10] 2025010 > student_gender [1] "Female" "Male" "Female" [4] "male" "Male" "Other" [7] "Female" "Prefer Not to Say" "Male" [10] "Female" > course_credits [1] 16 14 12 16 10 15 16 12 14 15 > hs_gpa [1] 3.85 3.35 3.70 3.25 3.60 4.10 3.95 3.15 3.50 3.45 >

> #4 .b. > student_data_frame <- data.frame(student_id, student_gender, course_cred its, hs_gpa) > student_data_frame student_id student_gender course_credits hs_gpa 1 2025001 Female 16 3.85 2 2025002 Male 14 3.35 3 2025003 Female 12 3.70 4 2025004 Male 16 3.25 5 2025005 Male 10 3.60 6 2025006 Other 15 4.10 7 2025007 Female 16 3.95 8 2025008 pPrefer Not to Say 12 3.15 9 2025009 Male 14 3.50 10 2025010 Female 15 3.45 >

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