Question

The file "bodytemp.csv" contains normal body temperature readings (degrees Fahrenheit) and heart rates (beats per minute) of 65 males (coded by 1) and 65 females (coded by 2).

(a) For both males and females, make scatterplots of heart rate versus body temperature. Comment on the relationship or lack thereof.

(b) Does the relationship for males appear to be the same as that for females? Examine this question graphically, by making a scatterplot showing both females and males and identifying females and males by different plotting symbols.

(c) For the males, fit a linear regression to predict heart rate from temperature. Plot the residuals versus temperature and comment on whether the relationship is linear. Find the estimated slope and its standard error.

(d) Repeat the above for females.

(Include Python code in answer)

Answer 1

To explore the relationship between heart rate and body temperature in males and females, we would create gender-specific scatterplots, fit linear regression models, analyze residuals, and compare slopes and standard errors.

Step-by-step explanation:

Scatterplots and Linear Regression in Python

To analyze the relationship between heart rate and body temperature for both males and females using the bodytemp.csv dataset, we would perform the following steps:

• Create scatterplots for males and females separately to visualize the relationship between heart rate and body temperature.
• Make a combined scatterplot with different plotting symbols for males and females to compare relationships.
• Fit a linear regression model for males to predict heart rate from temperature, calculate the slope and its standard error, and plot the residuals.
• Repeat the linear regression process for females, including a calculation of the slope and its standard error, and plot the residuals.

During the analysis, it is important to evaluate the linear relationship and potential influential points that might affect the regression results. Residual plots help us assess the linearity of the relationship. By comparing the estimated slopes and their standard errors between genders, we can draw conclusions about the strength and similarity of the relationships.