Intro Stats + MyStatLab Access Code
Intro Stats + MyStatLab Access Code
4th Edition
ISBN: 9780321891242
Author: De Veaux, Richard
Publisher: Pearson College Div
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Chapter 23, Problem 60E

Property assessments The following software output provides information about the Size (in square feet) of 18 homes in Ithaca, New York, and the city’s assessed Value of those homes.

Chapter 23, Problem 60E, Property assessments The following software output provides information about the Size (in square , example  1

Dependent variable is Value

R-squared = 32.5%

s = 4682 with 18 – 2 = 16 degrees of freedom

Chapter 23, Problem 60E, Property assessments The following software output provides information about the Size (in square , example  2

Chapter 23, Problem 60E, Property assessments The following software output provides information about the Size (in square , example  3

Chapter 23, Problem 60E, Property assessments The following software output provides information about the Size (in square , example  4

Chapter 23, Problem 60E, Property assessments The following software output provides information about the Size (in square , example  5

  1. a) Explain why inference for linear regression is appropriate with these data.
  2. b) Is there a significant association between the Size of a home and its assessed Value? Test an appropriate hypothesis and state your conclusion.
  3. c) What percentage of the variability in assessed Value is explained by this regression?
  4. d) Give a 90% confidence interval for the slope of the true regression line, and explain its meaning in the proper context.
  5. e) From this analysis, can we conclude that adding a room to your house will increase its assessed Value? Why or why not?
  6. f) The owner of a home measuring 2100 square feet files an appeal, claiming that the $70,200 assessed Value is too high. Do you agree? Explain your reasoning.
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Chapter 23 Solutions

Intro Stats + MyStatLab Access Code

Ch. 23 - Prob. 8ECh. 23 - Prob. 9ECh. 23 - Prob. 10ECh. 23 - Prob. 11ECh. 23 - 12. Shoot to score, double overtime One of the...Ch. 23 - Prob. 13ECh. 23 - Prob. 14ECh. 23 - Prob. 15ECh. 23 - Prob. 16ECh. 23 - Prob. 17ECh. 23 - Prob. 18ECh. 23 - Prob. 19ECh. 23 - Prob. 20ECh. 23 - Prob. 21ECh. 23 - Prob. 22ECh. 23 - Prob. 23ECh. 23 - Prob. 24ECh. 23 - Prob. 25ECh. 23 - Prob. 26ECh. 23 - Prob. 27ECh. 23 - Prob. 28ECh. 23 - Prob. 29ECh. 23 - Prob. 30ECh. 23 - Prob. 31ECh. 23 - Prob. 32ECh. 23 - Prob. 33ECh. 23 - Prob. 34ECh. 23 - Fuel economy A consumer organization has reported...Ch. 23 - 36. SAT scores How strong was the association...Ch. 23 - Prob. 37ECh. 23 - 38. SATs, part II Consider the high school SAT...Ch. 23 - 39. Fuel economy, part III Consider again the data...Ch. 23 - 40. SATs, again Consider the high school SAT...Ch. 23 - Cereals A healthy cereal should be low in both...Ch. 23 - Brain size Does your IQ depend on the size of your...Ch. 23 - Prob. 43ECh. 23 - Prob. 44ECh. 23 - Prob. 45ECh. 23 - Prob. 46ECh. 23 - Ozone and population The Environmental Protection...Ch. 23 - Prob. 48ECh. 23 - Prob. 49ECh. 23 - 50. More sales and profits Consider again the...Ch. 23 - Prob. 51ECh. 23 - Crawling Researchers at the University of Denver...Ch. 23 - 53. Body fat Do the data shown in the table below...Ch. 23 - Prob. 54ECh. 23 - Midterms The data set below shows midterm and...Ch. 23 - Prob. 56ECh. 23 - Prob. 57ECh. 23 - All the efficiency money can buy 2011 A sample of...Ch. 23 - Education and mortality The following software...Ch. 23 - Property assessments The following software output...Ch. 23 - Prob. 61ECh. 23 - Prob. 62E
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