Seperating males and females
males <- dat[dat$Sex==1,]
females <- dat[dat$Sex==2, ]
min(males$Beats)
## [1] 58
max(males$Beats)
## [1] 86
mean(males$Beats)
## [1] 73.36923
sd(males$Beats)
## [1] 5.875184
median(males$Beats)
## [1] 73
quantile(males$Beats)
## 0% 25% 50% 75% 100%
## 58 70 73 78 86
min(females$Beats)
## [1] 57
max(females$Beats)
## [1] 89
mean(females$Beats)
## [1] 74.15385
sd(females$Beats)
## [1] 8.105227
median(females$Beats)
## [1] 76
quantile(females$Beats)
## 0% 25% 50% 75% 100%
## 57 68 76 80 89
hist(males$Beats, col="Blue", xlab= "Resting heart rate of males")
hist(females$Beats, col="Pink", xlab= "Resting heart rate of females")
qqnorm(males$Beats)
qqnorm(females$Beats)
boxplot(males$Beats, females$Beats, xlab= "Resting heart rate of males Resting heart rate of females")
Similarities: Males and females have similar min of heart rates.
Differences: Males have lower max of hear rates and lower median than females. Females have larger interquartile range than male.
dat <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv")
males <- dat[dat$Sex==1,]
females <- dat[dat$Sex==2, ]
min(males$Beats)
max(males$Beats)
mean(males$Beats)
sd(males$Beats)
median(males$Beats)
quantile(males$Beats)
min(females$Beats)
max(females$Beats)
mean(females$Beats)
sd(females$Beats)
median(females$Beats)
quantile(females$Beats)
hist(males$Beats, col="Blue", xlab= "Resting heart rate of males")
hist(females$Beats, col="Pink", xlab= "Resting heart rate of females")
qqnorm(males$Beats)
qqnorm(females$Beats)
boxplot(males$Beats, females$Beats, xlab= "Resting heart rate of males Resting heart rate of females")