Question

please peovide coding in R:

with a data of 13 variables and 200 observations

Using the variable CLASS, test at 5% significance level to test the claim that the

proportions of Freshmen, Sophomores, Juniors, and Seniors are the same.

2. Repeat part (a) for the variable COLLEGE.

RLM ENGLISH MATH COMP 21 16 25 839SSESSOR 8 F 17 F N H ABCD 1 SEX HSP GPA AGE CREDITS CLASS COLLEGE MAJOR RESIDENCY TYPE 2 Transfer Blochm Resident F 75 2.39 22 A&S 78 Junior New Geog A&S Resident 3 M 63 3.37 21 90 Senior 4 New F Resident 77 2.63 22 112 Senior Bus Acct New Socstd 5 M Resident 21 66 2.77 52 Sophomore Educ New 6 Chem Resident 86 3.79 22 M 123 Senior A&S 7 M 61 Junior Resident New 21 CS 96 3.34 A&S 64 2.81 23 Freshman 20 A&S New Unded Resident 9 Math F 22 104 Senior 78 3.09 A&S New Resident Resident 39 Sophomore A&S Soc 63 1.91 10 M New 20 11 F 51 2.61 23 80 Junior A&S New Art Resident 12F 65 3.17 20 47 Sophomore A&S Unded Resident New 13 F 94 3.79 22 101 Senior Nurs Nursng Transfer Resident 14 M 54 3.14 20 57 Sophomore Bus Mktg Resident New 15 F 76 2.21_-22 121_Senior__ Bus Acct_ Resident_-_New 16 F 71 3.12 21 96 Senior Educ SpEd Nonresident New 74 3.42 22 137 Senior Educ ElEd Resident 18 F 80 3.25 21 63 Junior Nurs Nursng Nonresident New 19 M 55 2.34 21 100 Senior A&S Engl Resident New 20 F 61 2.76 19 32 Sophomore A&S Biolgy Resident New 21 M 66 1.95 19 30 Sophomore A&S CS . Resident New 22 F 89 2.59 20 27 Freshman Bus Busadm Resident New 23 M 90 3.58 22 125 Senior A&S Engl Resident New 24 M 86 2.67 23 110 Senior Bus Mgmt Resident New 25 F 43 2.1 23 49 Sophomore A&S Art Resident New 26 M 82 3.1 -19 28 Freshman A&S Unded Resident New 27 M 47 2.78 22 104 Senior Bus Busadm Resident New 28 M 92 3.76 21 105 Senior A&S CS Resident New 29 F 57 3.33 20 26 Freshman Educ E lEd Resident New 30 F 90 3.28 21 54 Sophomore A&S Engl Resident New 31 F 55 2.33 24 102 Senior A&S Unded Resident Readmit 32 M 56 2.45 23 136 Senior A&S Comm Nonresident New 67 3.56 19 36 Sophomore Nurs Nursng Nonresident New 34 M 96 3.13 19 34 Sophomore Bus Acct Resident New 35 M 63 4 18 18 Freshman A&S Unded Nonresident New 36 F 83 3.17 20 62 Junior Nurs Nursng Resident New 37 M 61 3.03 22 109 Senior ABS Comm Resident New 38 M 79 2.82 19 30 Sophomore Educ Phymat Resident Transfer 39 F 60 2.89 20 58 Sophomore Bus Acct Resident Transfer 40 M 79 3.66 21 109 Senior Educ Engl Resident New 41 F 62 2.43 27 153 Senior Hss Musthr Resident Transfer 42 M 91 3.07 19 30 Sophomore Bus Resident New 43 F 77 3.48 20 53 Sophomore Hiss Socwrk Resident 44 F 95 3.31 19 31 Sophomore Educ Biolgy Resident New 45 F BO 3.63 21 99 Senior A&S Psych Nonresident New 46 M 48 2.41 20 29 Freshman Bus Auct Resident 47 F 84 2.93 21 90 Senior ASS Psych Resident New 48 F 97 3.75 19 34 Sophomore A&S Prepha Nonresident New 40 M 35 2.19 21 87 Junior Hiss Head Nonresident Transfer 50 F 69 2.95 21 99 Senior A&S Span Resident New 51 F 70 2.37 21 69 Junior ASS Psych Nonresident New 52 M 85 3.51 20 62 Junior Mgmt Resident New 53 F 94 3.29 23 151 Senior Educ Music Resident New 54 M 65 3.84 20 59 Sophomore ABS Biolgy Resident 55 M 87 3.14 21 59 Sophomore A&S Preopt Nonresident New 56 M 19 2.79 22 108 Senior ASS Polsci Nonresident Transfer 33 F Now 8852389822822&SARE! New Focus Sample

Answer 1

Using some dummy data the R code is built . You need to use your data and try it out. The interpretation of the result is also explained. For both the variable you need to do the same thing.

Creating dummy data Please upload your data into the code and try it out. Since the data is not given in copy ready format, I using dummy data just to show how is done. Class_vector <- sample(c("Freshmen", "Sophomores", "Juniors", "Seniors"), size = 200, replace = T) data_df <- data.frame ("Class" = Class_vector) head(data_df) Class ## 1 Freshmen ## 2 Seniors ## 3 Juniors ## 4 Juniors ## 5 Sophomores ## 6 Freshmen Finding the proportion for each category in class ### Count of students in each type tablel <- table (data_df$Class) tablel Freshmen Juniors Seniors Sophomores 47 ### Prop of students in each type prop_class <- prop.table (tablel) prop_class Freshmen 0.205 Juniors 0.270 Seniors Sophomores 0.290 0.235

Using chisqaure test of goodness of fit chisq.test(prop_class, p= c(0.25, 0.25, 0.25, 0.25)) ### we use 0.25 since we want to check if the distribution is qual for all classes ## Warning in chisq.test (prop_class, p = c(0.25, 0.25, 0.25, 0.25)): Chi- ## squared approximation may be incorrect ## Chi-squared test for given probabilities ## data: prop_class ## X-squared = 0.017, df = 3, p-value = 0.9994 Ho: The distribution of the students for all the class is equal. H1: The distribution of the students for all the class is different. We see that the pvalue from the test If the pvalue is greater than 0.05, we fail reject the null hypothesis and conclude that the distribution is equal. If the pvalue is less than 0.05, we reject the null hypothesis and conclude that the distribution is not equal In this case, the distribution is equal. Please note : You need to try this for your own data. Incase you get any error while code. post the error in the comment and I will try to help you out