New Semester Started Get 50% OFF Study Help! --h --m --s Claim Now

Question Answers

Textbooks

Find textbooks, questions and answers

Oops, something went wrong!

Change your search query and then try again

Result Not Found

Books FREE
Study Help
Tutors
AI Study Planner NEW
Sell Books

Search
Sign In
Register

study help
business
intro stats

Stats Data And Models 3rd Canadian Edition Richard De Veaux, Paul Velleman, David Bock, Augustin Vukov, Augustine Wong - Solutions

5. Abalone Abalones are edible sea snails that include over 100 species. A researcher is working with a model that uses the number of rings in an Abalone’s shell to predict its age. He finds an observation that he believes has been miscalculated. After deleting this outlier, he redoes the
4. Revenue and ticket sales The concert production company of Exercise 2 made a second scatterplot, this time relating Total Revenue to Ticket Sales.a) Describe the relationship between Ticket Sales and Total Revenue.b) How are the results for the two venues similar?c) How are they different? Total
3. Market segments The analyst in Exercise 1 tried fitting the regression line to each market segment separately and found the following:What does this say about her concern in Exercise 1? Was she justified in worrying that the overall model Jan = $612.07 + 0.403 Dec might not accurately summarize
2. Revenue and talent cost A concert production company examined its records. The manager made the following scatterplot. The company places concerts in two venues,a smaller, more intimate theater (plotted with blue circles) and a larger auditorium-style venue (red x’s).a) Describe the
1. Credit card spending An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January (Jan) is related to their spending in December (Dec): The assumptions and conditions of the linear regression seemed to be satisfied and an analyst was about to
67. Regressing Test scores over the years in an introductory statistics course have shown a 0.6 correlation between term test and final exam. Suppose test and exam both have a mean of 70 with similar standard deviations.a) Predict the exam score of someone who gets 85 on the test.b) Predict the
66. Math and gender 2009 Below are mean PISA (Programme for International Student Assessment) math scores for samples of 15-year-old male and female students from a number of randomly selected schools in each of various OECD (Organization for Economic Cooperation and Development) and other
65. Immigrant commuters Recent immigrants are more likely than Canadian-born to use public transit. Below are data for selected Census Metropolitan Areas (CMA) on the percentage of individuals who commute to work by public transit, for recent immigrants ( a) Plot the immigrant percentage versus
64. Ontario interprovincial migration 2015 Below are data showing the net interprovincial migration each year for Ontario (number arriving minus number leaving). The data are not for calendar years, but for a one-year period ending in the displayed year.Year Ontario Net Migration 1979 –4 325 1980
63. Brakes The table below shows stopping distances in metres for a car tested three times at each of five speeds. We hope to create a model that predicts stopping distance from the speed of the car.Speed (km/h) Stopping Distances (m) 32 19.5, 18.9, 18.0 48 34.8, 36.0, 32.0 64 46.7, 52.1, 50.3 80
62. Gators Wildlife researchers monitor many wildlife populations by taking aerial photographs. Can they estimate the weights of alligators accurately from the air? Here is a regression analysis of the weight of alligators (in pounds) and their length (in inches) based on data collected from
61. Hard water In an investigation of environmental causes of disease, data were collected on the annual mortality rate (deaths per 100 000) for males in 61 large towns in England and Wales. In addition, the water hardness was recorded as the calcium concentration (parts per million, ppm) in the
60. Heptathlon 2012 again We saw the data for the women’s 2012 Olympic heptathlon in Exercise 59. Are the two jumping events associated? Perform a regression of the long jump results on the high jump results. Set aside in your analysis the last place (points) finisher, an apparent outlier.a)
59. Heptathlon 2012 We discussed the women’s 2012 Olympic heptathlon in Chapter 5. Here are the results from the high jump (metres), 800-metre run (seconds), and long jump (metres) for the women who successfully completed all three events in the 2012 Olympics:Athlete Country Points High Jump Long
58. Body fat, again Would a model that uses the person’s waist size be able to predict the % Body Fat more accurately than one that uses a person’s weight? Using the data in Exercise 57, create and analyze that model.
57. Body fat It is difficult to accurately determine a person’s body fat percentage without immersing him or her in water. Researchers hoping to find ways to make a good estimate immersed 20 male subjects, then measured their waists and recorded their weights.a) Create a model to predict % Body
56. Birthrates 2010 The following table shows the number of live births per 1000 population in the United States, starting in 1965. (National Center for Health Statistics (2010). Data for United States in 2010.)a) Make a scatterplot and describe the general trend in Birthrates. (Enter Year as years
55. Climate change 2013 The earth’s climate is getting warmer. The most common theory attributes the increase to an increase in atmospheric levels of carbon dioxide (CO2), a greenhouse gas. Here is a scatterplot showing the mean annual CO2 concentration in the atmosphere, measured in parts per
54. Candy 2009 The table below shows the increase in Halloween candy sales over a 6-year period as reported by the National Confectioners Association (www.candyusa.com). Using these data, estimate the amount of candy sold in 2009. Discuss the appropriateness of your model and your faith in the
53. New York bridges We saw in this chapter that in Tompkins County, NY, older bridges were in worse condition than newer ones. Tompkins is a rural area. Is this relationship true in New York City as well? Here are data on the Safety Score (as measured by the state Department of Transportation) and
52. Cost of living 2013 Numbeo.com lists the cost of living (COL) for many cities around the world. These rankings scale New York City as 100, and express the cost of living in other cities as a percentage of the New York cost. For example, the table below shows 25 of the most expensive cities in
51. A second helping of burgers In Exercise 49, you created a model that can estimate the number of calories in a burger when the fat content is known.a) Explain why you cannot use that model to estimate the fat content of a burger with 600 calories.b) Using an appropriate model, estimate the fat
50. Chicken Chicken sandwiches are often advertised as a healthier alternative to beef because many are lower in fat. Tests on 11 brands of fast food chicken sandwiches produced the following summary statistics and scatterplot from a graphing calculatoa) Do you think a linear model is appropriate
49. Burgers In the last chapter’s exercises, you examined the association between the amounts of fat and calories in fast-food hamburgers. Here are the data:a) Create a scatterplot of Calories vs. Fat.b) Interpret the value of R2 in this context.c) Write the equation of the line of regression.d)
48. Veggie burgers Recently Burger King introduced a meat-free burger. The nutrition label is shown here. a) Use the regression model created in this chapter, Fat = 8.4 + 0.91 Protein, to predict the fat content of this burger from its protein content.b) What is its residual? How would you explain
47. More used cars 2013 Use the advertised prices for Toyota Corollas given in Exercise 45 to create a linear model for the relationship between a car’s age and its price.a) Find the equation of the regression line.b) Explain the meaning of the slope of the line.c) Explain the meaning of the
46. Drug abuse In the exercises of the last chapter you examined results of a survey conducted in the United States and 10 countries of Western Europe to determine the percentage of teenagers who had used marijuana and other drugs. Below is the scatterplot. Summary statistics showed that the mean
45. Used cars 2013 Classified ads at www.auto123.com (on July 22, 2013) offered used Toyota Corollas for sale in central Ontario. Listed below are ages and advertised prices for some Corolla CEs with automatic transmission:a) Make a scatterplot for these data.b) Describe the association between age
44. Success, part 2 Based on the statistics for college freshmen given in Exercise 42, what SAT score might be expected among freshmen who attained a first-term GPA of 3.0?
43. SAT, take 2 Suppose we wanted to use SAT math scores to estimate verbal scores based on the information in Exercise 41.a) What is the correlation?b) Write the equation of the line of regression predicting verbal scores from math scores.c) In general, what would a positive residual mean in this
42. Success in college Many U.S. colleges use SAT scores in the admissions process because they believe these scores provide some insight into how a high-school student will perform at the college level. Suppose the entering freshmen at a certain college have mean combined SAT score of 1833, with
41. SAT scores The SAT is a test often used in the U.S. as part of an application to college. SAT scores are between 200 and 800. Tests are given in both math and verbal areas. Doing the SAT-Math problems also involves the ability to read and understand the questions, but can a person’s verbal
40. SI jinx Players in any sport who are having great seasons—turning in performances that are much better than anyone might have anticipated—often are pictured on the cover of Sports Illustrated. Frequently, their performances then falter somewhat, leading some athletes to believe in a
39. ESP People who claim to “have ESP” participate in a screening test in which they have to guess which of several images someone is thinking of. You and a friend both took the test. You scored two standard deviations above the mean, and your friend scored one standard deviation below the
38. More misinterpretations A Sociology student investigated the association between a country’s literacy rate and life expectancy, then drew the conclusions listed below. Explain why each statement is incorrect. (Assume that all the calculations were done properly.)a) The literacy rate
37. Misinterpretations A Biology student who created a regression model to use a bird’s height when perched for predicting its wingspan made these two statements. Assuming the calculations were done correctly, explain what is wrong with each interpretation.a) My R2 of 93% shows that this linear
36. What slope again? If you create a regression model for estimating the height of a pine tree (in centimetres) based on the circumference of its trunk (in centimetres), is the slope most likely to be 0.1, 1, 10, or 100? Explain.
35. What slope? If you create a regression model for predicting the weight of a car (in pounds) from its length (in feet), is the slope most likely to be 3, 30, 300, or 3000? Explain.
34. Last inning 2010 Refer again to the regression analysis for average attendance and games won by American League baseball teams, seen in Exercise 30.a) Write the equation of the regression line.b) Estimate the Average Attendance for a team with 50 Wins.c) Interpret the meaning of the slope of
33. Last cigarette Take another look at the regression analysis of tar and nicotine content of the cigarettes in Exercise 29.a) Write the equation of the regression line.b) Estimate the nicotine content of cigarettes with 4 milligrams of tar.c) Interpret the meaning of the slope of the regression
32. Second inning 2010 Consider again the regression of Average Attendance on Wins for the baseball teams examined in Exercise 30.a) What is the correlation between Wins and Average Attendance?b) What would you predict about the Average Attendance for a team that is 2 standard deviations above
31. Another cigarette Consider again the regression of nicotine content on tar (both in milligrams) for the cigarettes examined in Exercise 29.a) What is the correlation between tar and nicotine?b) What would you predict about the average nicotine content of cigarettes that are two standard
30. Attendance 2013, revisited In the previous chapter, you looked at the relationship between the number of wins by American League baseball teams and the average attendance at their home games for the 2013 season. Here are the scatterplot, the residuals plot, and part of the regression
29. Cigarettes Is the nicotine content of a cigarette related to the “tars”? A collection of data (in milligrams) on 29 cigarettes produced the scatterplot, residual plot, and regression analysis shown:a) Do you think a linear model is appropriate here? Explain.b) Explain the meaning of R2 in
28. Lots of money Consider the Ottawa-Gatineau census data from Exercise 22 again. The regression analysis gives the model Average income = $23 129 + 527.4 Degree.a) Explain what the slope of the line says about average income and percent with degree.b) What average income would you predict for a
27. More real estate Consider the Toronto downtown condo data from Exercise 21 again. The regression analysis gives the model Price = 49.30 + 0.37 Size.a) Explain what the slope of the line says about condo prices and condo size.b) What asking price would you predict for a 1000-square-foot condo in
26. More money The regression of average income on percent with degree for census tracts in Ottawa-Gatineau, as described in Exercise 22, had R2 = 54.2%.a) What is the correlation between average income and percent with degree?b) What would you predict about the average income of a census tract
25. Real estate redux The regression of price on size of homes in Toronto, as described in Exercise 21, had R2 = 70.2%.a) What is the correlation between size and price?b) What would you predict about the price of a home one standard deviation above average in size?c) What would you predict about
24. Money again The regression of average income on percent with degree for Ottawa-Gatineau census tracts, as described in Exercise 22, had R2 = 54.2%. Write a sentence (in context, of course) summarizing what the R2 value says about this regression.
23. Real estate again The regression of price on size of condos in Toronto, as described in Exercise 21, had R2 = 70.2%. Write a sentence (in context, of course) summarizing what the R2 value says about this regression.
22. Money and degrees The 2001 Canadian Census provides data on a number of variables for each census tract (neighbourhood). For example, we can find the average income and percent with a Bachelor’s degree for each of the 237 census tracts in Ottawa-Gatineau. A regression to predict average
20. Least squares II Consider the four points (200, 1950), (400, 1650), (600, 1800), and (800, 1600). The least squares line is yn = 1975 - 0.45x. Explain (or show) what least squares means using these data as a specific example. 21. Real estate The Re/Max August/Sept 2008 Market Report lists the
19. Least squares Consider the four points (10, 10), (20, 50), (40, 20), and (50, 80). The least squares line is yn = 7.0 + 1.1x. Explain (or show) what least squares means using these data as a specific example.
18. Residuals II Tell what each of the residual plots below indicates about the appropriateness of the linear model that was fit to the data.
17. Residuals Tell what each of the residual plots below indicates about the appropriateness of the linear model that was fit to the data. b) HH
16. More regression equations Fill in the missing information in the table below. X ST y Sy = b+ bx a) 30 4 18 6 -0.2 b) 100 18 60 10 0.9 c) d) 0.8 50 15 18 4 |= -10 + 15x -0.6 30 2x = -
15. Regression equations Fill in the missing information in the table below. I ST y Sy = b + bx a) 10 2 20 3 0.5 b) 2 0.06 7.2 1.2 -0.4 c) 12 6 -0.8 200-4x d) 2.5 1.2 100 =-100 + 50x
14. Disk drives 2014, residuals again Here is a scatterplot of the residuals from the regression of the hard drive prices on their sizes from Exercise 6.a) Are any assumptions or conditions violated? If so, which ones?b) What would you recommend about this regression? Residuals 300 100 -100 -300 0
13. Residual plots Here are residual plots (residuals plotted against predicted values) for three linear regression models. Indicate which condition appears to be violated (linearity, outlier, or equal spread) in each case. a) Residual 15+ 11 10 5 0 + 4 % -5 -10 + -10 0 10 20 30 40 50 60 70 Fitted
12. Disk drives encore For the hard drive data of Exercise 6, find and interpret the value of R2 .
11. Bookstore sales last time For the regression model for the bookstore of Exercise 5, what is the value of R2 and what does it mean?
10. Disk drives 2014, residuals Here are the residuals for a regression of Price on Capacity for the hard drives of Exercise 6. (Based on the hand-computed coefficients.) People Working Residual Capacity Residual 2 0.07 0.50 285.16 3 0.16 1.0 234.07 7 -1.49 2.0 123.88 9 -2.32 3.0 -20.27 10 0.77 4.0
9. Bookstore sales once more Here are the residuals for a regression of Sales on Number of Sales People Working for the bookstore of Exercise 5: Number of Sales
8. Sophomore slump again? An online investment blogger advises investing in mutual funds that have performed badly the past year because “regression to the mean tells us that they will do well next year.” Is he correct?
7. Sophomore slump? A CEO complains that the winners of his “rookie junior executive of the year” award often turn out to have less impressive performance the following year. He wonders whether the award actually encourages them to slack off. Can you offer a better explanation?
6. Disk drives 2014 again Recall the data on disk drives we saw in Chapter 6, Exercise 4. Suppose we want to predict Price from Capacity. Number of Sales People Working Sales (in $1000) 2 10 3 11 7 13 9 14 10 18 10 20 12 20 15 22 16 22 20 26 x = 10.4 y = 17.6 SD(x) = 5.64 SD(y) = 5.34 r = 0.965a)
5. Bookstore sales revisited Recall the data we saw in Chapter 6, Exercise 3 for a bookstore. The manager wants to predict Sales from Number of Sales People Working.
4. Residual interpretations The newborn grandson of one of the authors was 48 cm long and weighed 3 kg. According to the regression model of Exercise 3, what was his residual? What does that say about him?
3. Least squares interpretations A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.94 + 0.1875 length. Explain in words what this model means. Should new parents (who tend to worry) be concerned if their
2. True or false II If false, explain briefly.a) Some of the residuals from a least squares linear model will be positive and some will be negative.b) Least Squares means that some of the squares of the residuals are minimized.c) We write yn to denote the predicted values and y to denote the
1. True or false If false, explain briefly.a) We choose the linear model that passes through the most data points on the scatterplot.b) The residuals are the observed y-values minus the y-values predicted by the linear model.c) Least squares means that the square of the largest residual is as small
52. HDI and phones 2010 In Exercise 50, we examined the relationship between GDPPC and the Human Development Index for a large number of countries. The number of phone subscribers per 100 people is also associated with economic progress in a country. Here’s a scatterplot of phone subscribers per
51. Mandarin or Cantonese 2011 Below are data on Canadian cities showing mother-tongue counts from the 2011 census:a) Find the correlation between these two mother-tongue counts. Are you surprised that the correlation is so high? Explain.b) Plot Cantonese speaker count versus Mandarin speaker
50. Human Development Index 2010 The United Nations Development Programme (UNDP) uses the Human Development Index (HDI) in an attempt to summarize in one number the progress in health, education, and eco- nomics of a country. In 2010, the HDI was as high as 0.938 for Norway and as low as 0.14 for
49. Planets (more or less) On August 24, 2006, the International Astronomical Union voted that Pluto is not a planet. Some members of the public have been reluctant to accept that decision. Let’s look at some of the data. Is there any pattern to the locations of the planets? The table shows the
48. Interprovincial migration 2015 Below are data showing the net interprovincial migration each year for Ontario and Alberta (the number arriving minus the number leaving). Note that each year actually stands for a non-calendar year period ending in that particular year.Year Ontario Alberta
47. Census at school The International CensusAtSchool Project collects data on primary and secondary school students from various countries, including Canada. We selected a random sample of 111 Canadian secondary school students age 14 and over. Below are the first four rows of the 111-row
46. Obvious correlations Looking at the largest 152 urban areas in Canada, the correlation between the number of renter-occupied dwellings and number of owner-occupied dwellings per urban area is 0.955, while the correlation between the percentage of renter-occupied dwellings and percentage of
45. Bigger and bigger According to the UK National Sizing Survey, women’s average body-size measurements have increased over time as follows:a) Calculate all possible correlations among the four variables.b) Plot the body-size measurement sizes against each other and against time. Describe the
44. Ontario migration 2015 Below are data showing the net interprovincial migration each year for Ontario (number arriving minus number leaving):a) Calculate the correlation between Ontario net migration and year.b) A reporter claimed that the low correlation between year and migration shows that
43. Thrills III For the roller coaster data in Exercise 41:a) Explain why in looking for a variable that explains rank, you will be hoping for a negative correlation.b) Do any of the provided variables provide a strong predictor for roller coaster rank?c) What other (unaccounted for) variables
42. Thrills II For the roller coaster data in Exercise 41:a) Examine the relationship between Initial Drop and Max Speed.b) Examine the relationship between Initial Drop and Height.c) What conclusions can you safely draw about the initial drop of a roller coaster? Is Initial Drop strongly
41. Thrills 2011 Since 1994, the Best Roller Coaster Poll (www.ushsho.com/bestrollercoasterpoll.htm) has been ranking the world’s best roller coasters. In 2011, Bizarro earned the top steel coaster rank for the sixth straight year. Here are data on the top 10 steel coasters from this poll:What do
40. Sample survey A California polling organization is checking its database to see if the three data sources they used sampled the same zip codes (five-digit U.S. postal codes). The variable Datasource = 1 if the data source is MetroMedia, 2 if the data source is DataQwest, and 3 if it’s
39. Baldness and heart disease Medical researchers followed 1435 middle-aged men for a period of five years, measuring the amount of baldness present (none = 1, little = 2, some = 3, much = 4, extreme = 5) and presence of heart disease (no = 0, yes = 1). They found a correlation of 0.089 between
38. More correlation errors Students in the Economics class discussed in Exercise 37 also wrote these conclusions. Explain the mistakes they made.a) “There was a very strong correlation of 1.22 between life expectancy and GDP.”b) “The correlation between literacy rate and GDP was 0.83. This
37. Correlation errors Your Economics instructor asks the class to investigate factors associated with the gross domestic product (GDP) of nations. Each student examines a different factor (life expectancy, literacy rate, etc.) for a few countries and reports to the class. Apparently, some of your
36. Traffic headaches A study of traffic delays in 68 U.S. cities found the following relationship between total delays (in total hours lost) and mean highway speed:Is it appropriate to summarize the strength of association with a correlation? Explain. Total Delay() 600 000 450 000- 300 000- 150
35. Hard water In a study of streams in the Adirondack Mountains, the following relationship was found between the pH of the water and the water’s hardness (measured in grains)Is it appropriate to summarize the strength of association with a correlation? Explain. 80- HI 7.6 72- 6.8 6.4 125 250
34. Smart phones and life expectancy A survey of the world’s nations in 2010 shows a strong positive correlation between percentage of the country using smart phones and life expectancy in years at birth.a) Does this mean that smart phones are good for your health?b) What might explain the
33. Height and reading A researcher studies children in elementary school and finds a strong positive linear association between height and reading scores.a) Does this mean that taller children are generally better readers?b) What might explain the strong correlation?
32. Association V A researcher investigating the association between two variables collected some data and was surprised when he calculated the correlation. He had expected to find a fairly strong association, yet the correlation was near 0. Discouraged, he didn’t bother making a scatterplot.
31. Politics A candidate for office claims that “there is a correlation between television watching and crime.” Criticize this statement in statistical terms.
30. Second inning 2013 Perhaps fans are just more interested in teams that win. The displays below are based on American League teams for the 2013 season. (espn.go. com) (Use the data set Attendance_2013).a) Do winning teams generally enjoy greater attendance at their home games? Describe the
29. Attendance 2013 American League baseball games are played under the designated hitter rule, meaning that pitchers, often weak hitters, do not come to bat. Baseball owners believe that the designated hitter rule means more runs scored, which in turn means higher attendance. Is there evidence
28. Burgers II In the previous exercise, you analyzed the association between the amounts of fat and sodium in fast food hamburgers. What about fat and calories? Here are data for the same burgers. Analyze the association using correlation and scatterplots. Fat (g) 19 31 34 35 39 39 43 Calories 410
27. Burgers Fast food is often unhealthy because much of it is high in both fat and sodium. But are the two related? Here are the fat and sodium contents of several brands of burgers. Analyze the association between fat content and sodium. Fat (g) 19 31 34 35 39 39 43 Sedium (mg) 920 1500 1310 850
26. Drug abuse A survey was conducted in the United States and 10 countries of Western Europe to determine the percentage of teenagers who had used marijuana and other drugs. The results are summarized in the following table.a) Create a scatterplot.b) What is the correlation between the percent of
25. Fuel economy 2014 Here are advertised engine size (in litres) and gas mileage (estimated combined city and highway, in miles per gallon) for some 2014 vehicles.a) Make a scatterplot for these data.b) Describe the direction, form, and strength of the plot.c) Find the correlation between engine
24. Vehicle weights The Minnesota Department of Transportation hoped that they could measure the weights of big trucks without actually stopping the vehicles by using a newly developed “weight-in-motion” scale. To see if the new device was accurate, they conducted a calibration test. They

Showing 4100 - 4200 of 5937

First
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Last

Step by Step Answers

Services

Sitemap
Fun
Definitions
Become Tutor
Used Textbooks
Study Help Categories
Recent Questions
Expert Questions
Campus Wear
Sell Your Books

Company Info

Security
Copyrights
Privacy Policy
Terms & Conditions
SolutionInn Fee
Scholarship
Online Quiz
Give Feedback, Get Rewards

Get In Touch

About Us
Contact Us
Career
Jobs
FAQ
Student Discount
Campus Ambassador

Secure Payment

Download Our App

© 2026 SolutionInn. All Rights Reserved