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Quiz 5 Eamon Kraft 2023-10-17 Problem 1: (Exercise 6.1.14) 6 points (a, 2pt) DataSetName1<-read.csv("Swimmers_Ex6_1_4.csv", header=F) mean(DataSetName1 V1)sd(DataSet NamelV1) Results are: Mean: 52.64761 Standard Deviation: 7.655977 for (b, 2pt) hist(DataSetName1\$V1, breaks=15) "Added to end of the file" for (c, 2pt) "An outlier can be found between 110 and 120 in the dataset as displayed in the histgram™ Problem 2: (Exercise 6.4.9) — 4 points var1<-read.csv(*HighDose_Ex6_4_9.csv",header=F) var2<-read.csv("Control_Ex6_4_9.csv",header=F") boxplot(var1V1,var2v1) "Dose Summary" "Control Summary" Min: 12.9 Min: 15.8 First Qu: 23.7 First Qu: 153.9 Median: 45.0 Median: 326.8 Mean: 52.65 Mean: 575.3 Third Qu: 69.6 Third Qu: 654.7 Max: 134.9 Max: 3010.2 Problem 3: (Exercise 6-89) (a, 2pt) DataSetName<-read.csv("Climate_Ex6_5_4.csv") plot(DataSetNameYear,DataSetNameTempAnomaly, xlab="Year", ylab="Temperature(c)") (b, 4pt) plot(DataSetNameYear,DataSetNameCO2,xlab = "Year" ylab = "CO2(PPmv)) (c, 4pt) par(mar = ¢(5,4.5,1,4.5)) plot(DataSetNameYear,DataSetNameTempAnomaly,xlab ="Year",ylab = "TempAnomoly(c)",type="I', col="red') par(new=True) plot(DataSetNameYear,DataSetNameCO2,xlab="Year",ylab="CO2(PPmVv" type=" axes=F,col="blue') axes(4)
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