Chapter 3: Q 76. (page 210)
One child in the Mumbai study had height 59 cm and arm span 60 cm. This child’s residual is
a. −3.2 cm.
b. −2.2 cm.
c. −1.3 cm.
d. 3.2 cm.
e. 62.2 cm.
Short Answer
The correct option is (a)
Chapter 3: Q 76. (page 210)
One child in the Mumbai study had height 59 cm and arm span 60 cm. This child’s residual is
a. −3.2 cm.
b. −2.2 cm.
c. −1.3 cm.
d. 3.2 cm.
e. 62.2 cm.
The correct option is (a)
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Get started for freeMore Olympic athletes In Exercises 5 and 11, you described the relationship between height (in inches) and weight (in pounds) for Olympic track and field athletes. The scatterplot shows this relationship, along with two regression lines. The regression line for the shotput, hammer throw, and discus throw athletes (blue squares) is y^=−115+5.13x. The regression line for the remaining athletes (black dots) is y^=−297+6.41x
a. How do the regression lines compare?
b. How much more do you expect a 72-inch discus thrower to weigh than a 72-inch sprinter?
What’s my grade? In Professor Friedman’s economics course, the correlation
between the students’ total scores prior to the final examination and their final exam scores is r = 0.6. The pre-exam totals for all students in the course have a mean of 280 and a standard deviation of 30. The final exam scores have a mean of 75 and a standard deviation of 8. Professor Friedman has lost Julie’s final exam but knows that her total before the exam was 300. He decides to predict her final exam score from her pre-exam total.
a. Find the equation for the least-squares regression line Professor Friedman should use to make this prediction.
b. Use the least-squares regression line to predict Julie’s final exam score.
c. Explain the meaning of the phrase “least squares” in the context of this question.
d. Julie doesn’t think this method accurately predicts how well she did on the final exam. Determine r2. Use this result to argue that her actual score could have been much higher (or much lower) than the predicted value.
Movie candy Is there a relationship between the amount of sugar (in grams) and the number of calories in movie-theater candy? Here are the data from a sample of 12 types of candy:
a. Sketch a scatterplot of the data using sugar as the explanatory variable.
b. Use technology to calculate the equation of the least-squares regression line for predicting the number of calories based on the amount of sugar. Add the line to the scatterplot from part (a).
c. Explain why the line calculated in part (b) is called the “least-squares” regression line.
Age and height A random sample of 195 students was selected from the United Kingdom using the Census At School data selector. The age x (in years) and height y (in centimeters) were recorded for each student. Here is a scatterplot with the least-squares regression line y^=106.1+4.21x. For this model, s = 8.61 and r2 = 0.274.
a. Calculate and interpret the residual for the student who was 141 cm tall at age 10.
b. Interpret the slope of the least-squares regression line.
c. Interpret the value of s.
d. Interpret the value of r2.
Suppose that a tall child with an arm span of 120 cm and a height of 118 cm was added to the sample used in this study. What effect will this addition have on the correlation and the slope of the least-squares regression line?
a. Correlation will increase, and the slope will increase.
b. Correlation will increase, and the slope will stay the same.
c. Correlation will increase, and the slope will decrease.
d. Correlation will stay the same, and the slope will stay the same.
e. Correlation will stay the same, and the slope will increase.
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