3rd Edition

ISBN: 9780135188927

Author: Gould, Robert, Ryan, Colleen N. (colleen Nooter)

Publisher: Pearson,

Concept explainers

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as p…

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Textbook Question

Chapter 14, Problem 14SE

Simulated Data Figure A shows a scatterplot of some simulated data, and Figure B shows a residual plot of the same data. Is the linear regression model appropriate for these data? Why or why not? Assume the observations are independently measured.

Chapter 14, Problem 14SE, Simulated Data Figure A shows a scatterplot of some simulated data, and Figure B shows a residual , example 1

Chapter 14, Problem 14SE, Simulated Data Figure A shows a scatterplot of some simulated data, and Figure B shows a residual , example 2

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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Chapter 14, Problem 13SE

Chapter 14, Problem 15SE

Chapter 14 Solutions

Introductory Statistics

Ch. 14 - Predicting Test Scores A professor tells his class...Ch. 14 - Used-Car Values A student wishes to buy a used...Ch. 14 - Height and Age (Example 1) A doctor says he can...Ch. 14 - Units and Semesters The registrar at a small...Ch. 14 - Prob. 5SE Ch. 14 - Prob. 6SE Ch. 14 - Prob. 7SE Ch. 14 - Prob. 8SE Ch. 14 - Semesters and Credits (Example 4) Figure A shows a...Ch. 14 - Prob. 10SE

Ch. 14 - Salaries Figure A shows a scatterplot of the...Ch. 14 - Prob. 12SE Ch. 14 - Wages of Twins Figure A shows a scatterplot of...Ch. 14 - Simulated Data Figure A shows a scatterplot of...Ch. 14 - Prob. 15SE Ch. 14 - Movie Budgets Do movies with bigger budgets tend...Ch. 14 - Education of Parents (Example 7) Each of 29...Ch. 14 - Education of Parents Refer to exercise 14.17 and...Ch. 14 - Student and Parent Heights A random sample of 29...Ch. 14 - Trash The weight of trash (in pounds) produced by...Ch. 14 - Prob. 21SE Ch. 14 - Prob. 22SE Ch. 14 - Trash and Confidence Intervals The output provided...Ch. 14 - Movie Budgets In exercise 14.16 you examined the...Ch. 14 - Predicted GPA A student who has been accepted by...Ch. 14 - Used BMWs A used-car dealer is purchasing 50 used...Ch. 14 - Predicted Height (Example 9) A mother wants to...Ch. 14 - Predicted GPA A dean of students at a college...Ch. 14 - Loggers A logging company has the diameter of each...Ch. 14 - Prob. 30SE Ch. 14 - House Prices (Example 10) Figure A contains the...Ch. 14 - Math SAT Score and GPA Figure A shows information...Ch. 14 - Height and Weight A scatterplot of the heights and...Ch. 14 - Waist Size and Weight A scatterplot of the waist...Ch. 14 - GPA and SAT The figure shows 95#37; prediction...Ch. 14 - Shoes and Heights The scatterplot shows shoe size...Ch. 14 - Height and Weight A scatterplot of the heights and...Ch. 14 - Waist Size and Weight A scatterplot of the waist...Ch. 14 - Baseball Players Figure A shows a scatterplot with...Ch. 14 - Predicting Education Figure A shows a scatterplot...Ch. 14 - Life Expectancy and Gestation Periods for Animals...Ch. 14 - Prob. 42CRE

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Life 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?2300
Demand 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 2.00
Cellular Phone Subscribers The table shows the numbers of cellular phone subscribers y in millions in the United States from 2008 through 2013. Source: CTIA- The Wireless Association Year200820092010201120122013Number,y270286296316326336 (a) Find the least squares regression line for the data. Let x represent the year, with x=8 corresponding to 2008. (b) Use the linear regression capabilities of a graphing utility to find a linear model for the data. How does this model compare with the model obtained in part a? (c) Use the linear model to create a table of estimated values for y. Compare the estimated values with the actual data.

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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

Simulated Data Figure A shows a scatterplot of some simulated data, and Figure B shows a residual plot of the same data. Is the linear regression model appropriate for these data? Why or why not? Assume the observations are independently measured.

Solution Summary: The author explains that the linear regression model is not appropriate for the given data as the conditions of constant variation are not met.

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Chapter 14 Solutions

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