Module 13 Standard Error and Residual Plots Classwork
The relationship between height and arm-span measurement (in cm) was investigated by a group of
students (in 2010). Forty subjects were measured and the data was analyzed.
Computer technology gave the following results:
Least squares regression equation: Height = 7.333. + 0.949 (Arm Span)
r = 0.788
r 2 = 0.621
se = 4.8 cm
The domain of the explanatory variable (arm span) was: 145 cm to 180 cm
Answer the following questions. . Make sure to use appropriate units and complete sentences.
1. Explain the standard error se in context.
2. One of the subjects (Trevor) had an arm span of 176.5 cm. Use the linear regression equation to
predict his height.
3. Trevor’s actual height was 169.5 cm. Calculate the residual (error). Explain in context using a complete
sentence.
4. The standard error is shown to be 4.8 cm. What is the difference between this error and the error
found in problem 7 (from the residual)?
5. Match the scatterplot with the residual plot.
6. Which of the above scatterplots could a linear regression equation be used to make predictions?
Explain.