1. Estimate the correlation between the span of the writing hand and the span of

Question

1. Estimate the correlation between the span of the writing hand and the span of the non-writing hand. What do you conclude?

2. Plot the span of the writing hand versus the non-writing hand for males. Use a different symbol and/or color to plot the same the same association for

females on the same graph.

Please provide the R code for the above questions

X Sex Wr.Hnd NW.Hnd Pulse Smoke Height Age 1 Male 21.4 21 63 Never 180 19 2 Male 19.5 19.4 79 Never 165 18.083 3 Female 16.3 16.2 44 Regul 152.4 23.5 4 Female 15.9 16.5 99 Never 167.64 17.333 5 Male 19.3 19.4 55 Never 180.34 19.833 6 Male 18.5 18.5 48 Never 167 22.333 7 Female 17.5 17 85 Heavy 163 17.667 9 Female 13 12.5 77 Never 165 18.167 10 Female 18.5 18 75 Never 173 18.25 11 Female 17.5 17.1 73 Never 167 18.417 12 Male 22 21.5 73 Never 200 18.5 13 Male 20 20.5 57 Never 187.96 19.667 15 Female 16 16 66 Never 155 18.75 16 Female 13 13 98 Never 180.34 17.417 17 Male 18.5 19 81 Regul 187 17.917 18 Female 19.1 19 61 Occas 170 19.167 19 Male 22.2 21 80 Occas 190 18 22 Female 19.6 19.7 92 Never 178 17.5 24 Male 19.5 20.5 87 Regul 177.8 17.583 26 Female 19.5 18.5 67 Never 167 18.667 27 Male 18.9 19.1 84 Never 170 17.75 28 Male 18.1 18.2 49 Never 168 21.167 29 Male 23.2 23.3 49 Heavy 171 20.917 30 Male 16 15.5 101 Never 154.94 17.167 31 Male 19.7 20.1 83 Regul 180.34 17.75 32 Male 18.8 18.2 91 Never 180 17.5 33 Female 19.5 20.2 91 Never 155 17.5 34 Female 16.4 16.5 73 Never 152 18.333 35 Male 18.5 18.5 72 Never 165 18.5 36 Female 17.2 16.7 49 Never 170.18 21.167 37 Female 19.4 19.6 63 Never 175.26 19.083 38 Female 17 17.3 41 Never 157 35.833 40 Female 18 17.5 87 Never 170 17.583 42 Male 17 17.5 67 Regul 179.1 18.667 43 Male 22.5 22.6 47 Regul 187.96 23 44 Female 16.9 16 50 Never 158 20.5 45 Male 21 20.9 81 Never 177 17.917 46 Female 16.5 17 97 Never 167.64 17.417 48 Male 18.5 19 42 Never 170 23.833 50 Male 20.5 20.5 40 Regul 172.72 36.583 51 Female 16.5 17 40 Never 168 73 52 Male 19.1 19.1 51 Never 177 19.917 54 Female 17.5 17.5 49 Heavy 170 20.667 55 Female 17.7 17 100 Never 167 17.25 56 Female 15.5 15.4 101 Never 157.48 17.167 57 Male 20 19.5 58 Regul 190 19.417 58 Male 21 20.7 90 Never 172.72 17.5 60 Female 18 17.5 66 Never 165 18.667 61 Male 19 18.5 94 Never 189 17.417 62 Female 17.6 17.3 82 Never 168.5 17.75 63 Female 19.5 19.2 77 Never 170 18.167 64 Male 21.5 21.6 40 Never 172.72 70.417 66 Female 19 18.8 100 Never 172.72 17.25 67 Male 18.9 19.1 40 Never 180.34 43.833 68 Female 17.5 18 82 Never 157.48 17.75 69 Female 19 18.5 100 Never 170 17.25 71 Female 15.4 16.4 71 Occas 160.02 18.5 72 Male 18.5 18.5 73 Never 171 18.333 73 Male 19.2 18.9 51 Never 176.5 20.167 75 Male 17.7 17.7 64 Never 182.88 18.833 76 Male 21.3 20.8 48 Heavy 179 22.833 77 Male 17.5 17.5 68 Never 180 18.583 78 Female 16 15.5 93 Never 162.56 17.417 79 Female 18.5 18 89 Never 172 17.5 80 Female 17.5 17 80 Never 157 18 81 Female 18 17.8 102 Never 168.9 17.083 82 Male 18 18.5 65 Never 175 18.75 84 Male 18.5 18 82 Never 180.34 17.833 85 Male 19.2 19.6 76 Never 190.5 18.167 86 Male 21.5 21.2 74 Never 184 18.25 87 Female 16.5 16.9 42 Occas 169.2 29.083 88 Female 17.5 17.5 45 Never 166.5 23.25 89 Male 17.5 17 57 Never 165 19.5 90 Male 19.5 20.2 42 Never 185.42 32.667 92 Female 17.6 17.8 99 Never 160.02 17.25 93 Female 18.7 18 55 Never 170 19.833 94 Male 17 17.5 50 Never 165 20.417 95 Male 18.2 19.8 58 Never 185 19.333 96 Male 18 18.5 50 Never 173 20.333 97 Male 19.5 19.5 59 Never 167 19.25 98 Male 19 19.5 45 Occas 172 23.417 100 Male 20.5 20 44 Never 173 23.583

Explanation / Answer

###Set Your working directory and keep raw data in csv format in that place####

###Reading data####
newdata <- read.csv(file="data.csv",head=TRUE,sep=",")
newdata
###Attaching Data###
attach(newdata)

###Getting column names####
names(newdata)
##"X" "Sex" "Wr.Hnd" "NW.Hnd" "Pulse" "Smoke" "Height" "Age"##

################## A ####################
cor(newdata$Wr.Hnd,newdata$NW.Hnd,method ="pearson")
##0.966347

##Conclusion: Wr.Hnd and NW.Hnd have a strong linear relationship.##

######## B ########

### Splitting the data into male and female###
y=split(newdata,newdata$Sex)

### Plotting for male###
plot(y$Male$Wr.Hnd,y$Male$NW.Hnd,col="red",xlab="Wr.Hnd",ylab = "NW.Hnd",main = "Plot of span of the writing hand versus
the non-writing hand for males & females")

###Plotting for females###
points(y$Female$Wr.Hnd,y$Female$NW.Hnd,col="blue")

###Adding legend###
legend(17,22,c("Male","Female"),c("Red","Blue"))

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