Mind on Statistics
5th Edition
ISBN: 9781285463186
Author: Jessica M. Utts, Robert F. Heckard
Publisher: Brooks Cole
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Textbook Question
Chapter 3, Problem 3.19E
A regression equation for y = handspan (cm) and x =height (inches) was discussed in Section 3.2. If the roles of the variables are reversed and only women are considered, the regression equation is
Average height = 51.1 ÷ 0.7 (Handspan).
- Interpret the slope of 0.7 in terms of how height changes as handspan increases.
- What is the estimated average height of women with a handspan of 20 cm?
- Molly has a handspan of 20 cm and is 66.5 inches tall. What is the prediction error (residual) for Molly?
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Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation:
y = 58.9-0.00749x, where x represents weight. Complete parts (a) through (d).
Click the icon to view the car data.
The site to your captio V.UVITU.
D. The slope is -0.00749 and the y-intercept is 58.9.
c. What is the predictor variable?
...
OA. The predictor variable is highway fuel consumption, which is represented by x.
OB. The predictor variable is highway fuel consumption, which is represented by y.
C. The predictor variable is weight, which is represented by x.
OD. The predictor variable is weight, which is represented by y.
d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994
lb?
The best predicted value of highway fuel consumption of a car that weighs 2994 lb is
(Round to one decimal place as needed.)
mi/gal.
In constructing the regression equation for predicting
electricity bills (BILLS) from number of people in an area
(AREA), it was calculated that the slope is 57.35 and it was
known that the mean BILL is PhP 1,327.21 and the mean
NUMBER is 6.31. What is the value of the intercept?
O None of the Choices
O PhP 768.08
O PhP 965.33
O PhP 611.10
O PhP 884.55
After interviewing salespersons at Harley Davidson dealerships, a researcher has created a linear regression line to explain the relationship between a Harley Davidson motorcycle's age (x) and price (y). The regression has an = 87.7%. Write a sentence summarizing what says about this regression.
The age of the motorcycle explains 12.3% of the variation in price.
The age of the motorcycle explains 9.36% of the variation in price.
The age of the motorcycle explains 87.7% of the variation in price.
The price of the motorcycle explains 12.3% of the variation in age.
The price of the motorcycle explains 87.7% of the variation in age.
Chapter 3 Solutions
Mind on Statistics
Ch. 3 - For each of the following pairs of variables, is...Ch. 3 - For each of the following pairs of variables, is...Ch. 3 - The figure for this exercise is a scatter plot of...Ch. 3 - Prob. 3.4ECh. 3 - Prob. 3.5ECh. 3 - Prob. 3.6ECh. 3 - Prob. 3.7ECh. 3 - Prob. 3.8ECh. 3 - The data in the following table are the geographic...Ch. 3 - Refer to the latitude and temperature data in the...
Ch. 3 - Prob. 3.11ECh. 3 - The following table shows sex, height (inches),...Ch. 3 - Prob. 3.13ECh. 3 - Refer to Exercise 3.13 in which a regression...Ch. 3 - Prob. 3.15ECh. 3 - Prob. 3.16ECh. 3 - The equation for converting a temperature from x =...Ch. 3 - The average August temperatures (y) and geographic...Ch. 3 - A regression equation for y = handspan (cm) and x...Ch. 3 - Imagine a regression line that relates y average...Ch. 3 - Prob. 3.21ECh. 3 - The figure for Exercise 3.8 is a scatterplot of...Ch. 3 - Refer to Exercise 3.22. Predict the pulse rate...Ch. 3 - The average January temperatures (y) and...Ch. 3 - Prob. 3.25ECh. 3 - Prob. 3.26ECh. 3 - Prob. 3.27ECh. 3 - Remember that r2 can be expressed as a proportion...Ch. 3 - Prob. 3.29ECh. 3 - Prob. 3.30ECh. 3 - Prob. 3.31ECh. 3 - Prob. 3.32ECh. 3 - Prob. 3.33ECh. 3 - Explain how two variables can have a perfect...Ch. 3 - Prob. 3.35ECh. 3 - Prob. 3.36ECh. 3 - The figure for this exercise (below) shows four...Ch. 3 - Refer to the figure for the previous exercises. In...Ch. 3 - Prob. 3.39ECh. 3 - Prob. 3.40ECh. 3 - Prob. 3.41ECh. 3 - Prob. 3.42ECh. 3 - Prob. 3.43ECh. 3 - The correlation between latitude and average...Ch. 3 - Prob. 3.45ECh. 3 - Prob. 3.46ECh. 3 - In a regression analysis, the total sum of squares...Ch. 3 - Prob. 3.48ECh. 3 - Suppose you know that the slope of a regression...Ch. 3 - Prob. 3.50ECh. 3 - Prob. 3.51ECh. 3 - Prob. 3.53ECh. 3 - Prob. 3.54ECh. 3 - Refer back to Exercise 3.7 about stopping distance...Ch. 3 - Prob. 3.56ECh. 3 - Prob. 3.57ECh. 3 - Prob. 3.58ECh. 3 - Prob. 3.59ECh. 3 - Prob. 3.60ECh. 3 - Prob. 3.61ECh. 3 - Prob. 3.62ECh. 3 - Prob. 3.63ECh. 3 - Prob. 3.64ECh. 3 - Prob. 3.65ECh. 3 - Prob. 3.66ECh. 3 - Prob. 3.67ECh. 3 - Prob. 3.68ECh. 3 - Prob. 3.69ECh. 3 - Prob. 3.70ECh. 3 - Prob. 3.71ECh. 3 - Given tickets for traffic violations than drivers...Ch. 3 - Prob. 3.73ECh. 3 - Prob. 3.74ECh. 3 - Prob. 3.75ECh. 3 - Prob. 3.76ECh. 3 - Prob. 3.77ECh. 3 - Prob. 3.78ECh. 3 - Prob. 3.79ECh. 3 - The heights (inches) and foot lengths (cm) of 33...Ch. 3 - Prob. 3.81ECh. 3 - The winning time in the Olympic men’s 500-meter...Ch. 3 - Prob. 3.83ECh. 3 - Prob. 3.84ECh. 3 - Prob. 3.86ECh. 3 - Prob. 3.87ECh. 3 - Prob. 3.88ECh. 3 - Prob. 3.89ECh. 3 - Use the dataset ceodata0t on the companion website...Ch. 3 - Prob. 3.91ECh. 3 - Prob. 3.92ECh. 3 - Prob. 3.93ECh. 3 - Prob. 3.94ECh. 3 - Prob. 3.95ECh. 3 - Prob. 3.96ECh. 3 - Prob. 3.97ECh. 3 - Prob. 3.98ECh. 3 - Prob. 3.99ECh. 3 - Prob. 3.100E
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
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