51 lines
1.3 KiB
R
51 lines
1.3 KiB
R
library(mosaic)
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library(MASS)
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# Q1
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mean_days<-mean(~Days, data=quine)
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median_days<-median(~Days, data=quine)
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sd_days<-sd(~Days, data=quine)
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sk_days<-3 * (mean_days - median_days) / sd_days
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# Q2
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title<-"Days Absent Histogram"
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xtitle<-"Days Absent"
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ytitle<-"Frequency"
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hist(quine$Days, main=title, xlab=xtitle, ylab=ytitle)
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# Q3
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title<-"Box Plot Days Absent"
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xtitle<-"Days Absent"
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bwplot(~Days, data=quine, main=title, xlab=xtitle)
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# Q4
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median(quine$Days)
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# Q5
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title<-"Days Absent Grouped by Age"
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xtitle<-"Days Absent"
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ytitle<-"Age"
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bwplot(quine$Age ~ quine$Days, main=title, xlab=xtitle, ylab=ytitle)
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# Q6
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favstats(Days ~ Age + Sex, data=quine)
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# Q7
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quantile(Days ~ Lrn, data=quine, probs = c (.20, .40, .60, .80))
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quantile(Days ~ Eth, data=quine, probs = c (.20, .40, .60, .80))
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quantile(Days ~ Sex, data=quine, probs = c (.20, .40, .60, .80))
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# Q8
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f0_male<-filter(quine, Age=="F0" & Sex=="M")
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days_f0_male<-f0_male$Days
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percentiles<-rank(days_f0_male) / length(days_f0_male) * 100
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percentiles<-round(percentiles, 2)
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percentiles
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# Q9
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studentsOneMean<-quine |> filter(abs(scale(Days)) >= 1)
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studentsTwoMean<-quine |> filter(abs(scale(Days)) >= 2)
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studentsThreeMean<-quine |> filter(abs(scale(Days)) >= 3)
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nrow(studentsOneMean)
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nrow(studentsTwoMean)
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nrow(studentsThreeMean) |