Statistics: The Art and Science of Learning from Data (4th Edition)
4th Edition
ISBN: 9780321997838
Author: Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 13, Problem 64CP
To determine
Explain the difference in the slope of poverty, which is 28.33 for the two-predictor model and 14.95 after adding the third predictor to the model.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
Q1: Please use the data set to create a regression equation or a regression line that can reflect the relationship between wealth and level of education in CA counties.
NOTES: You are required to: 1) clearly state what is the dependent variable (Y) and what is the independent variable (X); 2) correctly calculate the associated slope and intercept.
Q2: Please predict the related median household income when there is 70% of population over 25 with BA degree and higher.
Median Household Income ($)
% of population over 25 with BA degree and higher
100,929
42.1
71,348
20.5
59,961
25.0
69,588
21.1
108,689
39.4
90,996
32.1
63,284
19.5
53,746
27.5
58,528
13.4
66,834
15.2…
The table below shows the number of years since 1995
and the price of milk.
春
6.
12
14
16
Years since 195 ()
Price of milk PO
(in dollars)
$2.62 $2.70 $2.78 $2.88 $3.15 53.40 $3.30 $3.57
The model P(t) = 0.06t + 2.52 represents the relationship
between the years, t, since 1995 and the price of milk,
P(t)
What are the interpretations of the Y intercept and the slopes in a multiple regression model?
Chapter 13 Solutions
Statistics: The Art and Science of Learning from Data (4th Edition)
Ch. 13.1 - Predicting weight For a study of female college...Ch. 13.1 - Prob. 2PBCh. 13.1 - Predicting college GPA For all students at Walden...Ch. 13.1 - Prob. 4PBCh. 13.1 - Does more education cause more crime? The FL Crime...Ch. 13.1 - Crime rate and income Refer to the previous...Ch. 13.1 - The economics of golf The earnings of a PGA Tour...Ch. 13.1 - Prob. 8PBCh. 13.1 - Controlling can have no effect Suppose that the...Ch. 13.1 - House selling prices Using software with the House...
Ch. 13.1 - Used cars The following data (also available from...Ch. 13.2 - Predicting sports attendance Keeneland Racetrack...Ch. 13.2 - Predicting weight Lets use multiple regression to...Ch. 13.2 - Prob. 14PBCh. 13.2 - Price of used cars For the 19 used cars listed in...Ch. 13.2 - Prob. 16PBCh. 13.2 - Softball data For the Softball data set on the...Ch. 13.2 - Slopes, correlations, and units In Example 2 on y...Ch. 13.2 - Predicting college GPA Using software with the...Ch. 13.3 - Predicting GPA For the 59 observations in the...Ch. 13.3 - Study time help GPA? Refer to the previous...Ch. 13.3 - Variability in college GPA Refer to the previous...Ch. 13.3 - Does leg press help predict body strength? Chapter...Ch. 13.3 - Prob. 24PBCh. 13.3 - Interpret strength variability Refer to the...Ch. 13.3 - Any predictive power? Refer to the previous three...Ch. 13.3 - Predicting pizza revenue Aunt Ermas Pizza...Ch. 13.3 - Prob. 28PBCh. 13.3 - Mental health again Refer to the previous...Ch. 13.3 - Prob. 30PBCh. 13.3 - House prices Use software to do further analyses...Ch. 13.4 - Body weight residuals Examples 47 used multiple...Ch. 13.4 - Strength residuals In Chapter 12, we analyzed...Ch. 13.4 - Prob. 34PBCh. 13.4 - Nonlinear effects of age Suppose you fit a...Ch. 13.4 - Prob. 36PBCh. 13.4 - Why inspect residuals? When we use multiple...Ch. 13.4 - College athletes The College Athletes data set on...Ch. 13.4 - House prices Use software with the House Selling...Ch. 13.4 - Prob. 40PBCh. 13.5 - U.S. and foreign used cars Refer to the used car...Ch. 13.5 - Prob. 42PBCh. 13.5 - Predict using house size and condition For the...Ch. 13.5 - Quality and productivity The table shows data from...Ch. 13.5 - Predicting hamburger sales A chain restaurant that...Ch. 13.5 - Prob. 46PBCh. 13.5 - House size and garage interact? Refer to the...Ch. 13.5 - Prob. 48PBCh. 13.5 - Comparing sales You own a gift shop that has a...Ch. 13.6 - Prob. 50PBCh. 13.6 - Prob. 51PBCh. 13.6 - Prob. 52PBCh. 13.6 - Prob. 53PBCh. 13.6 - Prob. 54PBCh. 13.6 - Prob. 55PBCh. 13.6 - Prob. 56PBCh. 13.6 - Prob. 57PBCh. 13.6 - Prob. 58PBCh. 13.6 - Prob. 59PBCh. 13 - House prices This chapter has considered many...Ch. 13 - Prob. 61CPCh. 13 - Prob. 62CPCh. 13 - Prob. 63CPCh. 13 - Prob. 64CPCh. 13 - Prob. 65CPCh. 13 - Prob. 66CPCh. 13 - Prob. 67CPCh. 13 - Prob. 68CPCh. 13 - Prob. 69CPCh. 13 - AIDS and AZT In a study (reported in the New York...Ch. 13 - Factors affecting first home purchase The table...Ch. 13 - Unemployment and GDP Refer to Exercise 13.67. When...Ch. 13 - Prob. 75CPCh. 13 - Prob. 76CPCh. 13 - Prob. 77CPCh. 13 - Prob. 78CPCh. 13 - Prob. 79CPCh. 13 - True or false: Slopes For data on y = college GPA,...Ch. 13 - Prob. 81CPCh. 13 - Lurking variable Give an example of three...Ch. 13 - Prob. 83CPCh. 13 - Prob. 84CPCh. 13 - Prob. 85CPCh. 13 - Logistic versus linear For binary response...Ch. 13 - Prob. 87CPCh. 13 - Prob. 88CPCh. 13 - Prob. 89CPCh. 13 - Prob. 90CPCh. 13 - Prob. 91CPCh. 13 - Prob. 92CPCh. 13 - Prob. 93CP
Knowledge Booster
Learn more about
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
- When Date Are Unevenly speed. If data are evenly spaced, we need only calculate differences to see whether the data are linear. But if data not evenly spaced, then we must calculate the average rate of change over each interval to see whether the data are linear. If the average rate of changes is constant, it is the slope of the linear function. This fact is used in Exercises 23 and 24. In the following table, show that the average rate of change is the same over each interval. This shows the data are linear, even though the differences in y are not constant. Then find a linear model for the data. x 1 2 5 6 y 7 10 19 22arrow_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardDemand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00arrow_forward
- When Date Are Unevenly speed. If data are evenly spaced, we need only calculate differences to see whether the data are linear. But if data are not evenly spaced, then we must calculate the average rate of change over each interval to see whether the data are linear. If the average rate of change is constant, it is the slope of the linear function. This fact is used in Exercises 23 and 24. In the following table, show that the average rate of change from 2 to 5 is not the same as the average rate of change from 5 to 6. This shows that the data are not linear, even though the differences in y are constant. x 1 2 5 6 y 3 6 9 12arrow_forwardA researcher is analyzing the relationship between various variables in housing data for 32 cities: median list prices of single family homes, condominium or co-ops, all homes, median household income, unemployment rate, and population. What is the regression equation for the model that predicts the list price of all homes using population as an explanatory variable?What is the interpretation of the slope? What is the interpretation of the intercept?arrow_forwardType the regression equation for “Area” and “Biomass” in context into your document. Interpret the slope of the regression line (in context of this data set) for “Area” and “Biomass”. is it meaningful to interpret the y-intercept for “Area” and “Biomass”? Why or why not?arrow_forward
- Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in xarrow_forwardAfter 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.arrow_forwardA grocery store is interested in how customers' income affects the amount of money they spend each week. A regression analysis is performed to test this analysis. The results of the analysis are that the intercept is $17.80 and the slope is 0.0012. The residual of one customer's weekly spending was $54.12. Is this household an example of over or under prediction and expenditures inverse or direct and is the relationship between income under-prediction, inverse under-prediction, direct over-prediction, direct over-prediction, inverse evidence of diet equity for this grocery store's customersarrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Trigonometry (MindTap Course List)TrigonometryISBN:9781305652224Author:Charles P. McKeague, Mark D. TurnerPublisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)AlgebraISBN:9781305071742Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Trigonometry (MindTap Course List)
Trigonometry
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY