Reading data

dat <- as.data.frame(read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv"))
male <- dat[1:65,3]
female <- dat[66:130,3]

Descriptive statistics

Sample min, sample max, sample mean, sample standard deviation, sample median, quartiles, histogram and normal probability plot for Male heart beats:

summary(male)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   58.00   70.00   73.00   73.37   78.00   86.00
sd(male)
## [1] 5.875184
hist(male, main ="Histogram of male beats",col="blue", xlab = "Male heart beats")

qqnorm(male, main ="Normal probability plot of male beats", xlab = "Theoretical Quantiles")

Comments on statistics of male beats: mean value is close to median value, both values could represent the whole group to some extent. 2nd Quartile covers less range compared to 3rd Quartile does, which indicates that more data is gathered in 2nd Quartile.

Histogram of male beats: This histogram generally follows the normal distribution. Heart beats between 70-75, 65-70, 75-80 rank the first three highest occurance frequency. A slew of samples tend to cluster around the sample mean, while only few samples are close to min and max.

Normal probability plot of male beats: This Quantile-Quantile Plot shows a quasi-linear trend, which implies that samples are generally normally distributed. This conclusion is consistent with the arguements on histogram.

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Sample min, sample max, sample mean, sample standard deviation, sample median, quartiles, histogram and normal probability plot for Female heart beats:

summary(female)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   57.00   68.00   76.00   74.15   80.00   89.00
sd(female)
## [1] 8.105227
hist(female, main ="Histogram of female beats", col="pink", xlab = "Female heart beats")

qqnorm(female, main ="Normal probability plot of female beats", xlab = "Theoretical Quantiles")

Comments on statistics of female beats: mean value is less close to median value compared to the male data. 3rd Quartile covers less range compared to 2nd Quartile does, which indicates that more data is gathered in 3rd Quartile.

Histogram of female beats: This histogram follows the normal distribution to a limited degree. Heart beats between 75-80, 80-85, 65-75 rank the first three highest occurance frequency. A slew of samples tend to cluster around the sample median, while only few samples are close to min and max. Histogram also exihibits left-skewness with more data on the left hand side.

Normal probability plot of female beats: This Quantile-Quantile Plot shows a limited linear trend, which implies that samples are not well normally distributed compared to male data. This conclusion is consistent with the arguements on histogram.

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Box plot of female/male heart beats:

boxplot(male, female, main= "Box plot of male/female heart beats", ylab= "male/female heart beat",names=c("Male","Female"))

Comments:

1. Difference between max and min in female case is larger than that in male case.

2. The median of male data is more close to the mean of the 2nd Quartile than the 3rd Quartile, while median of female data is more close to the mean of the 3rd Quartile than the 2nd Quartile.

3. Median of female case is larger than that of male case.

4. 3rd Quartile covers larger range compared to 2nd Quartile in male case, while 2nd Quartile covers larger range compared to 3rd Quartile in female case.

5. Point 3 indicates that more data is clustered within 2nd Quartile in male case, while more data is clustered within 3nd Quartile in female case.

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Raw R codes:

# All R code used in document
summary(male)
sd(male)

hist(male, main ="Histogram of male beats",col="blue", xlab = "male heart beat")
qqnorm(male, main ="Normal distribution of male beats", xlab = "male heart beat")

summary(female)
sd(female)

hist(female, main ="Histogram of female beats", col="pink", xlab = "female heart beat")
qqnorm(female, main ="Normal distribution of female beats", xlab = "female heart beat")

boxplot(male, female, main= "Box plot of male/female beats", ylab= "male/female heart beat",names=c("Male","Female"))