- Write and describe a multiple linear regression model equation
- Calculate and describe the unadjusted coefficient of determination
- Assess the model assumptions with a residual or a predicted values plot
Students in an introductory statistics class at The University of Queensland participated in a simple experiment.[1] The students took their own pulse rates. They were then asked to flip a coin. If the coin came up heads, they were to run in place for one minute. Otherwise, they sat for one minute. Afterward, everyone took their pulse rates again. The pulse rates and other physiological and lifestyle data were recorded in a data set called “Pulse Rate.” There are a total of 110 observations and 11 variables about the experiment.
The first research question we are interested in exploring is: “What is the relationship between weight and first pulse measurement? Is weight a useful predictor of first pulse rate?”
The second research question that we are interested in exploring is: “What is the relationship between weight and age on the first pulse measurement? Are weight and age useful predictors of the first pulse rate?”
- Wilson, R. J. (n.d.). Pulse rates before and after exercise. StatSci.org. http://www.statsci.org/data/oz/ms212.html ↵