Identify and describe the relationship between response and explanatory variables
Students in an introductory statistics class at The University of Queensland participated in a simple experiment.[1]
The variables in the data set are:
Variable
Description
ID
Identification number
Height
Height in centimeters (cm)
Weight
Weight in kilograms (kg)
Age
Age in years
Sex
Male/female
Smokes
Are you a regular smoker? (yes/no)
Alcohol
Are you a regular drinker? (yes/no)
Exercise
What is your frequency of exercise? (low, moderate, high)
GroupAssignment
Whether the student ran or sat between the first and second pulse measurements
Pulse1
First pulse measurement (rate per minute)
Pulse2
Second pulse measurement (rate per minute)
Year
Year of class (1993–1998)
The explanatory variable ([latex]x[/latex]) is the variable that is thought to explain or predict the response variable of a study.
The response variable ([latex]y[/latex]) measures the outcome of interest in the study. This variable is thought to depend in some way on the explanatory variable. It is often referred to as the “variable of interest” for the researcher. The explanatory variable is used to predict/calculate/determine the response variable.
The students are interested in building a model that can be used to estimate a student’s weight based on the student’s height.