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Question: Many variables have an impact on determining

Many variables have an impact on determining the price of a house. Among these are Living Area of the house (square feet) and number of Bathrooms. Information for a random sample of homes for sale in the Statesboro, GA, area was obtained from the Internet. Regression output modeling the asking Price with Living Area and number of Bathrooms gave the following result: Dependent Variable is: Price s = 67013 R-Sq = 71.1%
Many variables have an impact on determining the price of a house. Among these are Living Area of the house (square feet) and number of Bathrooms. Information for a random sample of homes for sale in the Statesboro, GA, area was obtained from the Internet. Regression output modeling the asking Price with Living Area and number of Bathrooms gave the following result:
Dependent Variable is: Price
s = 67013 R-Sq = 71.1%
1. Write the regression equation.
2. Explain in context what the coefficient of Living Area means.
3. The owner of a construction firm, upon seeing this model, says that the slope for bathrooms is too small. He says that when he adds another bathroom, it increases the value by more than $9530. Can you think of an explanation for his question?

1. Write the regression equation. 2. Explain in context what the coefficient of Living Area means. 3. The owner of a construction firm, upon seeing this model, says that the slope for bathrooms is too small. He says that when he adds another bathroom, it increases the value by more than $9530. Can you think of an explanation for his question?


> Rolling a fair six-sided die is supposed to randomly generate the numbers 1 through 6. Explain what random means in this context.

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> Here are the same three prices as in Exercise 15 but for 576 cities around the world. (Prices are all in US$ as of August 2016; data in COLall 2016.) 1. In general, which commodity is the most expensive? 2. Is a carton of eggs ever more expensive than a

> A company hoping to assess employee satisfaction surveys employees by assigning computer-generated random numbers to each employee on a list of all employees and then contacting all those whose assigned random number is divisible by 7. Is this a simple r

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> The company annual report states, Our survey shows that 87.34% of our employees are very happy working here. Comment on that claim. Use appropriate statistics terminology.

> The president of the university plans a speech to an alumni group. He plans to talk about the proportion of students who responded in the survey that they are the first in their family to attend college, but the first draft of his speech treats that prop

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> The company plans to have the head of each corporate division hold a meeting of their employees to ask whether they are happy on their jobs. They will ask people to raise their hands to indicate whether they are happy. What problems do you see with this

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> To help travelers know what to expect, researchers collected the prices of commodities in 16 cities throughout the world. Here are boxplots comparing the average prices of a bottle of water, a dozen eggs, and a cappuccino in the 16 cities (prices are all

> In Chapters 4 and 6 we’ve seen data Let look at data from the Hopkins Forest. Here a regression that models the maximum daily wind speed in terms of the average temperature and precipitation: Response variable is: Max wind (mph) R-squar

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> For the movies regression in Exercise 3, here is a histogram of the residuals. What does it tell us about the assumptions and conditions below? 1. Linearity Condition 2. Nearly Normal Condition 3. Equal Spread Condition

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> A middle manager at an entertainment company, upon seeing the analysis of Exercise 3, concludes that longer movies make more money. He argues that his company films should all be padded by 30 minutes to improve their gross. Explain the flaw in his interp

> What can predict how much a motion picture will make? We have data on 609 recent releases that includes the USGross (in $M), the Budget ($M), the Run Time (minutes), and the score given by the critics on the Rotten Tomatoes website. The first several ent

> The dataset Grades shows the five scores from an Introductory statistics course. Find a model for final exam score by trying all possible models with two predictor variables. Which model would you choose? Be sure to check the conditions for multiple regr

> We saw a model in Exercise 24 for the calorie count of a breakfast cereal. Can we predict the calories of a serving from its vitamin and mineral content? Here a multiple regression model of Calories per serving on its Sodium (mg), Potassium (mg), and Sug

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> Find data on the Internet (or elsewhere) for two or more groups. Make appropriate displays to compare the groups, and interpret what you find.

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> Several exercises in Chapter 7 showed that attendance Attendance at American League baseball games increased increases with the number of runs scored. But fans may respond more to winning teams than to high-scoring games. Here is a regression of average

> Hill running races up and down hills has a written history in Scotland dating back to the year 1040. Races are held throughout the year at different locations around Scotland. A recent compilation of information for 90 races (for which full information w

> Find an article in a newspaper, a magazine, or the Internet that compares two or more groups of data. 1. Does the article discuss the W? 2. Is the chosen display appropriate? Explain. 3. Discuss what the display reveals about the groups. 4. Does the arti

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> 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 shell to predict its age. He finds an observation that he believes has been miscalculated. After deleting this

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> Using data from 20 compact cars, a consumer group develops a model that predicts the stopping time for a vehicle by using its weight. You consider using this model to predict the stopping time for your large SUV. Explain why this is not advisable.

> Noting a recent study predicting the increase in cell phone costs, a friend remarks that by the time he a grandfather, no one will be able to afford a cell phone. Explain where his thinking went awry.

> Can you design a Simpson paradox? Two companies are vying for a city Best Local Employer award to be given to the company most committed to hiring local residents. Although both employers hired 300 new people in the past year, Company A brags that it des

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> Suppose you have fit a linear model to some data and now take a look at the residuals. For each of the following possible residuals plots, tell whether you would try a re-expression and, if so, why.

> Suppose you have fit a linear model to some data and now take a look at the residuals. For each of the following possible residuals plots, tell whether you would try a re-expression and, if so, why.

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> 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?

> 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 explanatio

> Recall the data on disk drives we saw in Chapter 6, Exercise 4. Look at data on disk drives in the table below. Suppose we want to predict Price from Capacity. 1. Find the slope estimate, b1. 2. What does it mean, in this context? 3. Find the intercept,

> Recall the data we saw in Chapter 6, Exercise 3 for a bookstore. Below are data for a bookstore. The manager wants to predict Sales from Number of Sales People Working. 1. Find the slope estimate, b1 2. What does it mean, in this context? 3. Find the int

> A company must decide which of two delivery services it will contract with. During a recent trial period, the company shipped numerous packages with each service and kept track of how often deliveries did not arrive on time. Here are the data: 1. Compare

> 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?

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> If false, explain briefly. 1. Some of the residuals from a least squares linear model will be positive and some will be negative. 2. Least squares means that some of the squares of the residuals are minimized. 3. We write y^ to denote the predicted value

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> 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.

> For the hard drive data of Exercise 6, find and interpret the value of R2.

> For the regression model for the bookstore of Exercise 5, what is the value of R2 and what does it mean?

> Here are the residuals for a regression of Price on Capacity for the hard drives of Exercise 6 (based on the hand-computed coefficients). 1. Which residual contributes the most to the sum that is minimized by the least squares criterion? 2. Five of the r

> If false, explain briefly. 1. We choose the linear model that passes through the most data points on the scatterplot. 2. The residuals are the observed y-values minus the y-values predicted by the linear model. 3. Least squares means that the square of t

> A study finds that during blizzards, online sales are highly associated with the number of snow plows on the road; the more plows, the more online purchases. The director of an association of online merchants suggests that the organization should encoura

> Most patients who undergo surgery make routine recoveries and are discharged as planned. Others suffer excessive bleeding, infection, or other postsurgical complications and have their discharges from the hospital delayed. Suppose your city has a large h

> A larger firm is considering acquiring the bookstore of Exercise 3. An analyst for the firm, noting the relationship seen in Exercise 3, suggests that when they acquire the store they should hire more people because that will drive higher sales. Is his c

> If we assume that the conditions for correlation are met, which of the following are true? If false, explain briefly. 1. A correlation of 0.02 indicates a strong, positive association. 2. Standardizing the variables will make the correlation 0. 3. Adding

> If we assume that the conditions for correlation are met, which of the following are true? If false, explain briefly. 1. A correlation of 0.98 indicates a strong, negative association. 2. Multiplying every value of x by 2 will double the correlation. 3.

2.99

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