Data621-HW1
MKunissery
February 3, 2019
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Question 1 :
The dataset teengamb concerns a study of teenage gambling in Britain. Make a numerical and graphical summary of the data, commenting on any features that you find interesting. Limit the output you present to a quantity that a busy reader would find sufficient to get a basic understanding of the data.
I would like to experiment the below questions
- What percentage of income do teens spend on gambling to indicate an issue
newdata = teengamb
newdata$income <- newdata$income * 52
newdata$poi <- (newdata$gamble / newdata$income)*100
hist(newdata$poi,xlab="percent of income to gambling")
(length(which(newdata$poi > 10)) / nrow(newdata) ) * 100## [1] 29.78723The result shows that about 30% of teens spend more than 10 percent of their income in gambling which is not good
- male & female gambling comparisons
plot(gamble ~ sex, newdata)
plot(sort(newdata$gamble), ylab = "Sorted Expenditure")
plot(newdata$gamble ~ newdata$verbal)
## question 1.3 The dataset prostate is from a study on 97 men with prostate cancer who were due to receive a radical prostatectomy. Make a numerical and graphical summary of the data as in the first question
data("prostate")
summary(prostate)## lcavol lweight age lbph
## Min. :-1.3471 Min. :2.375 Min. :41.00 Min. :-1.3863
## 1st Qu.: 0.5128 1st Qu.:3.376 1st Qu.:60.00 1st Qu.:-1.3863
## Median : 1.4469 Median :3.623 Median :65.00 Median : 0.3001
## Mean : 1.3500 Mean :3.653 Mean :63.87 Mean : 0.1004
## 3rd Qu.: 2.1270 3rd Qu.:3.878 3rd Qu.:68.00 3rd Qu.: 1.5581
## Max. : 3.8210 Max. :6.108 Max. :79.00 Max. : 2.3263
## svi lcp gleason pgg45
## Min. :0.0000 Min. :-1.3863 Min. :6.000 Min. : 0.00
## 1st Qu.:0.0000 1st Qu.:-1.3863 1st Qu.:6.000 1st Qu.: 0.00
## Median :0.0000 Median :-0.7985 Median :7.000 Median : 15.00
## Mean :0.2165 Mean :-0.1794 Mean :6.753 Mean : 24.38
## 3rd Qu.:0.0000 3rd Qu.: 1.1786 3rd Qu.:7.000 3rd Qu.: 40.00
## Max. :1.0000 Max. : 2.9042 Max. :9.000 Max. :100.00
## lpsa
## Min. :-0.4308
## 1st Qu.: 1.7317
## Median : 2.5915
## Mean : 2.4784
## 3rd Qu.: 3.0564
## Max. : 5.5829prostate$gleason <- factor(prostate$gleason)
prostate$svi <- factor(prostate$svi)
summary(prostate)## lcavol lweight age lbph
## Min. :-1.3471 Min. :2.375 Min. :41.00 Min. :-1.3863
## 1st Qu.: 0.5128 1st Qu.:3.376 1st Qu.:60.00 1st Qu.:-1.3863
## Median : 1.4469 Median :3.623 Median :65.00 Median : 0.3001
## Mean : 1.3500 Mean :3.653 Mean :63.87 Mean : 0.1004
## 3rd Qu.: 2.1270 3rd Qu.:3.878 3rd Qu.:68.00 3rd Qu.: 1.5581
## Max. : 3.8210 Max. :6.108 Max. :79.00 Max. : 2.3263
## svi lcp gleason pgg45 lpsa
## 0:76 Min. :-1.3863 6:35 Min. : 0.00 Min. :-0.4308
## 1:21 1st Qu.:-1.3863 7:56 1st Qu.: 0.00 1st Qu.: 1.7317
## Median :-0.7985 8: 1 Median : 15.00 Median : 2.5915
## Mean :-0.1794 9: 5 Mean : 24.38 Mean : 2.4784
## 3rd Qu.: 1.1786 3rd Qu.: 40.00 3rd Qu.: 3.0564
## Max. : 2.9042 Max. :100.00 Max. : 5.5829hist(prostate$lcavol, xlab = "Cancer Volume", main = "")
plot(density(prostate$lcavol, na.rm = TRUE), main = "")
plot(lcavol ~ lweight, prostate)
abline(lm(lcavol ~ lweight, prostate))
question 1.4
The dataset sat comes from a study entitled “Getting What You Pay For: The Debate Over Equity in Public School Expenditures.” Make a numerical and graphical summary of the data as in the first question.
data(sat)
summary(sat)## expend ratio salary takers
## Min. :3.656 Min. :13.80 Min. :25.99 Min. : 4.00
## 1st Qu.:4.882 1st Qu.:15.22 1st Qu.:30.98 1st Qu.: 9.00
## Median :5.768 Median :16.60 Median :33.29 Median :28.00
## Mean :5.905 Mean :16.86 Mean :34.83 Mean :35.24
## 3rd Qu.:6.434 3rd Qu.:17.57 3rd Qu.:38.55 3rd Qu.:63.00
## Max. :9.774 Max. :24.30 Max. :50.05 Max. :81.00
## verbal math total
## Min. :401.0 Min. :443.0 Min. : 844.0
## 1st Qu.:427.2 1st Qu.:474.8 1st Qu.: 897.2
## Median :448.0 Median :497.5 Median : 945.5
## Mean :457.1 Mean :508.8 Mean : 965.9
## 3rd Qu.:490.2 3rd Qu.:539.5 3rd Qu.:1032.0
## Max. :516.0 Max. :592.0 Max. :1107.0hist(sat$expend, xlab = "Expenditure", main = "")
plot(density(sat$expend, na.rm = TRUE), main = "")
plot(expend ~ ratio, sat)
abline(lm(expend ~ ratio, sat))
plot(expend ~ verbal, sat)
abline(lm(expend ~ verbal, sat))
question 1.5
The dataset divusa contains data on divorces in the United States from 1920 to 1996. Make a numerical and graphical summary of the data as in the first question
data("divusa")
summary(divusa)## year divorce unemployed femlab
## Min. :1920 Min. : 6.10 Min. : 1.200 Min. :22.70
## 1st Qu.:1939 1st Qu.: 8.70 1st Qu.: 4.200 1st Qu.:27.47
## Median :1958 Median :10.60 Median : 5.600 Median :37.10
## Mean :1958 Mean :13.27 Mean : 7.173 Mean :38.58
## 3rd Qu.:1977 3rd Qu.:20.30 3rd Qu.: 7.500 3rd Qu.:47.80
## Max. :1996 Max. :22.80 Max. :24.900 Max. :59.30
## marriage birth military
## Min. : 49.70 Min. : 65.30 Min. : 1.940
## 1st Qu.: 61.90 1st Qu.: 68.90 1st Qu.: 3.469
## Median : 74.10 Median : 85.90 Median : 9.102
## Mean : 72.97 Mean : 88.89 Mean :12.365
## 3rd Qu.: 80.00 3rd Qu.:107.30 3rd Qu.:14.266
## Max. :118.10 Max. :122.90 Max. :86.641hist(divusa$divorce, xlab = "DIVORCE", main = "")
plot(sort(divusa$divorce), ylab = "Sorted Divorce")
lmod10 <- lm(divorce ~ marriage, divusa)
coef(lmod10)## (Intercept) marriage
## 30.1081994 -0.2307625plot(divorce ~ femlab, divusa)
abline(lm(divorce ~ femlab, divusa))
plot(divorce ~ military, divusa)
abline(lm(divorce ~ military, divusa))