IE-5342 Assignment #2
Bradley Solomon
Last compiled on August 29, 2026 at 9:00 PM - CDT
1 Analysis & Source Data
Analysis of resting heart rate data for 65 randomly selected males and 65 randomly selected females.
The source data used in this analysis is shown below. Males are denoted by the number 1 and females the number 2 in the column titled Sex.
url<-"https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv"
csvdata<-read.csv(url)
rmarkdown::paged_table(csvdata)2 Male Data Analysis
2.1 Descriptive Statistics
2.1.1 Minimum Resting Heart Rate
male<-csvdata[csvdata$Sex==1, ]
malemin<-min(male[ ,3])
malemin<-as.character(malemin)
cat(paste(malemin,"BPM"))58 BPM2.1.2 Maximum Resting Heart Rate
malemax<-max(male[ ,3])
malemax<-as.character(malemax)
cat(paste(malemax,"BPM"))86 BPM2.1.3 Sample Mean
\[\overline{x}=\frac{\sum x_{i}}{n} \]
malemean<-round(mean(male[ ,3]),2)
malemean<-as.character(malemean)
cat(paste(malemean,"BPM"))73.37 BPM2.1.4 Sample Standard Deviation
\[s = \sqrt[]{\frac{\sum(x_{i}-\overline{x})^{2} }{n-1}} \]
malesd<-sd(male[ ,3])
malesd<-as.character(round(malesd,2))
cat(paste(malesd,"BPM"))5.88 BPM2.1.5 Sample Median
\[Median = \frac{n+1}{2}^{th} position \]
malemedian<-median(male[ ,3])
malemedian<-as.character(malemedian)
cat(paste(malemedian,"BPM"))73 BPM2.1.6 Quartiles
malequartile<-quantile(male[ ,3])
malequartile 0% 25% 50% 75% 100%
58 70 73 78 86 2.2 Histogram
hist(male[ ,3],
main = "Male Resting Heart Rate",
xlab = "Heart Rate (bpm)",
ylab = "Frequency",
col = "blue",
border = "black")
2.3 Normal Probability Plot
qqnorm(male[ ,3], main = "Male Resting Heart Rate Normal Probability Plot", xlab = "Theoretical Vales", ylab = "Sample Values (bpm)")
2.4 Male Data Analysis Comments
I think what is worth noticing with the resting heart rate data from the males sampled is the mean, standard deviation, and histogram. The data sampled from males resulted in a mean of 73 bpm with a standard deviation of 5.88 bpm. The majority of sampled values landed in that range of 65-80 bpm as shown in the histogram plot.
3 Female Data Analysis
3.1 Descriptive Statistics
3.1.1 Minimum Resting Heart Rate
female<-csvdata[csvdata$Sex==2, ]
femalemin<-min(female[ ,3])
femalemin<-as.character(femalemin)
cat(paste(femalemin,"BPM"))57 BPM3.1.2 Maximum Resting Heart Rate
femalemax<-max(female[ ,3])
femalemax<-as.character(femalemax)
cat(paste(femalemax,"BPM"))89 BPM3.1.3 Sample Mean
\[\overline{x}=\frac{\sum x_{i}}{n} \]
femalemean<-round(mean(female[ ,3]),2)
femalemean<-as.character(femalemean)
cat(paste(femalemean,"BPM"))74.15 BPM3.1.4 Sample Standard Deviation
\[s = \sqrt[]{\frac{\sum(x_{i}-\overline{x})^{2} }{n-1}} \]
femalesd<-sd(female[ ,3])
femalesd<-as.character(round(femalesd,2))
cat(paste(femalesd,"BPM"))8.11 BPM3.1.5 Sample Median
\[Median = \frac{n+1}{2}^{th} position \]
femalemedian<-median(female[ ,3])
femalemedian<-as.character(femalemedian)
cat(paste(femalemedian,"BPM"))76 BPM3.1.6 Quartiles
femalequartile<-quantile(female[ ,3])
femalequartile 0% 25% 50% 75% 100%
57 68 76 80 89 3.2 Histogram
hist(female[ ,3],
main = "Female Resting Heart Rate",
xlab = "Heart Rate (bpm)",
ylab = "Frequency",
col = "pink",
border = "black")
3.3 Normal Probability Plot
qqnorm(female[ ,3], main = "Female Resting Heart Rate Normal Probability Plot", xlab = "Theoretical Vales", ylab = "Sample Values (bpm)")
3.4 Female Data Analysis Comments
The results of the sampled female data had more variation than that of the male data. The standard deviation of the data was 8.11 with a sample mean of 76 bpm. Additionally the range of sampled values was larger than that of the male data. Typically women have a higher resting heart rate then men; therefore, the results of descriptive statistics shouldn’t be surprising when comparing the male versus the female data.
4 Box Plot Analysis
boxplot(male[ ,3],female[ ,3],names=c("Male","Female"),col=c("blue","pink"),ylab="Heart Rate (bpd)",main="Male vs. Female Resting Heart Rate")
4.1 Box Plot Comments
As shown on the box plot results, female data recorded in this study resulted in a larger range of resting heart rate values. Female heart rate data exceeded both the minimum and maximum measured values of the male participants. Something also worth noting the position of the median values for both groups. The male median (73 BPM) is slightly lower than the measured female median (76 BPM).
5 Complete R Code
# Analysis & Source Data
Analysis of resting heart rate data for 65 randomly selected males and 65 randomly selected females.
The source data used in this analysis is shown below. Males are denoted by the number 1 and females the number 2 in the column titled Sex.
url<-"https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv"
csvdata<-read.csv(url)
rmarkdown::paged_table(csvdata)
# Male Data Analysis
## Descriptive Statistics
### Minimum Resting Heart Rate
male<-csvdata[csvdata$Sex==1, ]
malemin<-min(male[ ,3])
malemin<-as.character(malemin)
cat(paste(malemin,"BPM"))
### Maximum Resting Heart Rate
malemax<-max(male[ ,3])
malemax<-as.character(malemax)
cat(paste(malemax,"BPM"))
### Sample Mean
$$\overline{x}=\frac{\sum x_{i}}{n} $$
malemean<-round(mean(male[ ,3]),2)
malemean<-as.character(malemean)
cat(paste(malemean,"BPM"))
### Sample Standard Deviation
$$s = \sqrt[]{\frac{\sum(x_{i}-\overline{x})^{2} }{n-1}} $$
malesd<-sd(male[ ,3])
malesd<-as.character(round(malesd,2))
cat(paste(malesd,"BPM"))
### Sample Median
$$Median = \frac{n+1}{2}^{th} position $$
malemedian<-median(male[ ,3])
malemedian<-as.character(malemedian)
cat(paste(malemedian,"BPM"))
### Quartiles
malequartile<-quantile(male[ ,3])
malequartile
## Histogram
hist(male[ ,3],
main = "Male Resting Heart Rate",
xlab = "Heart Rate (bpm)",
ylab = "Frequency",
col = "blue",
border = "black")
## Normal Probability Plot
qqnorm(male[ ,3], main = "Male Resting Heart Rate Normal Probability Plot", xlab = "Theoretical Vales", ylab = "Sample Values (bpm)")
## Male Data Analysis Comments
# Female Data Analysis
## Descriptive Statistics
### Minimum Resting Heart Rate
female<-csvdata[csvdata$Sex==2, ]
femalemin<-min(female[ ,3])
femalemin<-as.character(femalemin)
cat(paste(femalemin,"BPM"))
### Maximum Resting Heart Rate
femalemax<-max(female[ ,3])
femalemax<-as.character(femalemax)
cat(paste(femalemax,"BPM"))
### Sample Mean
femalemean<-round(mean(female[ ,3]),2)
femalemean<-as.character(femalemean)
cat(paste(femalemean,"BPM"))
### Sample Standard Deviation
femalesd<-sd(female[ ,3])
femalesd<-as.character(round(femalesd,2))
cat(paste(femalesd,"BPM"))
### Sample Median
femalemedian<-median(female[ ,3])
femalemedian<-as.character(femalemedian)
cat(paste(femalemedian,"BPM"))
### Quartiles
femalequartile<-quantile(female[ ,3])
femalequartile
## Histogram
hist(female[ ,3],
main = "Female Resting Heart Rate",
xlab = "Heart Rate (bpm)",
ylab = "Frequency",
col = "pink",
border = "black")
## Normal Probability Plot
qqnorm(female[ ,3], main = "Female Resting Heart Rate Normal Probability Plot", xlab = "Theoretical Vales", ylab = "Sample Values (bpm)")
# Box Plot Analysis
boxplot(male[ ,3],female[ ,3],names=c("Male","Female"),col=c("blue","pink"),ylab="Heart Rate (bpd)",main="Male vs. Female Resting Heart Rate")