17A

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)
Variable name Definition
id Identification number of the student
female Gender of the student (0 = male, 1 = female)
race Ethnic background of the student (1 = Hispanic, 2 = Asian, 3 = Black, 4 = White)
ses Socio-economic status of the student (1 = low, 2 = medium, 3 = high)
schtyp School type (1 = public, 2 = private)
prog Program type (1 = general, 2 = academic preparatory, 3 = vocational/technical)
read Score from test of reading
write Score from test of writing
math Score from test of math
science Score from test of science
socst Score from test of social studies
Estimate
Intercept 11.61550
math 0.4172
read 0.36542
Coefficients Estimate
Intercept 49.58930
Age (yrs) 0.16531
Weight (lbs) 0.22638
Height (in) 1.11680
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)
Coefficients Estimate
Intercept 86.96948
Weight 0.17002
Skill or Concept: I can . . . Questions to check your understanding Rating
from 1 to 5
Identify response and explanatory variables. 1, 2, 7, 8
Write the equation of the line of best fit for simple linear regression. 4
Interpret the slope in the context of the data. 5
Interpret the coefficient of determination. 6
Interpret a scatterplot of a response variable and one explanatory variable. 3

A scatterplot titled “Scatterplot of Pulse 1 and Weight,” with “Weight (kg)” on the x-axis and “Pulse 1” on the y-axis. The points are arranged in somewhat of a cluster. Points with lower x-values have a slight tendency to have higher y-values. A person in a wheelchair and wearing a disposable mask sitting at an outdoor table working on a laptop. A scatterplot titled “Scatterplot of Math and Science Scores for High School Students.” The x-axis is labeled “math test score” and the y-axis is labeled “science test score.” Points with higher x-values also tend to have higher y-values, with moderate consistency. A scatterplot titled “Scatterplot of Reading and Science Scores for High School Students.” The x-axis is labeled “reading test score” and the y-axis is labeled “science test score.” Points with higher x-values also tend to have higher y-values, with moderate consistency. A residual plot titled “Residuals vs. Fitted,” with “Fitted Value” on the x-axis and “Residual” on the y-axis. The points appear to have no pattern. A residual plot titled “Residuals vs. Math Test Scores,” with “Math Test Scores” on the x-axis and “Residuals” on the y-axis. The points appear to have no pattern. A residual plot titled “Residuals vs. Reading Test Scores,” with “Reading Test Scores” on the x-axis and “Residual” on the y-axis. The points appear to have no pattern.

Glossary

multiple linear regression model
a linear regression model with two or more explanatory variables.
partial slopes
the regression coefficients for explanatory variables in multiple linear regression.