3rd Edition

ISBN: 9780135163146

Author: Gould

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 4, Problem 66SE

Teacher Pay and High School Graduation Rates The scatterplot shows the average teacher pay and high school graduation percentage rate for each of the 50 states and the District of Columbia. The regression equation is also shown. (Source: 2017 World Almanac Book of Facts and higheredinfo.org)

Chapter 4, Problem 66SE, Teacher Pay and High School Graduation Rates The scatterplot shows the average teacher pay and high

a. Based on the scatterplot is the correlation between average teacher pay and high school graduation rate positive, negative, or near zero?

b. Should the regression equation be used to predict the high school graduation rate for a state with an average teacher salary of $ 60 , 000 ? If so, predict the graduation rate. If not, explain why the regression equation should not be used to make this prediction.

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Chapter 4, Problem 65SE

Chapter 4, Problem 67SE

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Spring is a peak time for selling houses. The file SpringHouses contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor.com website) Click on the datafile logo to reference the data. DATA file a. The Excel output for the estimated regression equation that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house: SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression statistics Regression Residual Total Multiple R R Square ANOVA Adjusted R Square Standard Error Observations 0.7429 0.5519 0.4907 61948.6931 Regression statistics Regression Residual Total df Intercept Sq Ft Beds Lower 95% 0.9353 -145129.5298 Intercept Baths 0.9528 -49383.5243 0.0180 Sq Ft Beds 0.0326 Does the estimated regression equation provide a good fit to the data? Explain. Hint: If R is greater than 45%, the…

Chapter 4 Solutions

INTRODUCTORY STATISTICS (LOOSELEAF)

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Solution Summary: The author explains that the scatterplot that represents the relationship between the teacher’s pay and the high school graduation rates is given.

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