Elementary Statistics Plus MyLab Statistics with Pearson eText -- Access Card Package (7th Edition) (What's New in Statistics)

7th Edition

ISBN: 9780134684901

Author: Ron Larson, Betsy Farber

Publisher: PEARSON

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Correlation

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 9.2, Problem 33E

In Exercises 33 and 34, (a) find the equation of the regression line, (b) construct a scatter plot of the data and draw the regression line, (c) construct a residual plot, and (d) determine whether there are any patterns in the residual plat and explain what they suggest about the relationship between the variables.

33. Chapter 9.2, Problem 33E, In Exercises 33 and 34, (a) find the equation of the regression line, (b) construct a scatter plot

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Chapter 9.2, Problem 32E

Chapter 9.2, Problem 34E

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(c) Because logistic regression predicts probabilities of outcomes, observations used to build a logistic regression model need not be independent. A. false: all observations must be independent B. true C. false: only observations with the same outcome need to be independent I ANSWERED: A. false: all observations must be independent. (This was marked wrong but I have no idea why. Isn't this a basic assumption of logistic regression)

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Spam filters are built on principles similar to those used in logistic regression. We fit a probability that each message is spam or not spam. We have several variables for each email. Here are a few: to_multiple=1 if there are multiple recipients, winner=1 if the word 'winner' appears in the subject line, format=1 if the email is poorly formatted, re_subj=1 if "re" appears in the subject line. A logistic model was fit to a dataset with the following output: Estimate SE Z Pr(>|Z|) (Intercept) -0.8161 0.086 -9.4895 0 to_multiple -2.5651 0.3052 -8.4047 0 winner 1.5801 0.3156 5.0067 0 format -0.1528 0.1136 -1.3451 0.1786 re_subj -2.8401 0.363 -7.824 0 (a) Write down the model using the coefficients from the model fit.log_odds(spam) = -0.8161 + -2.5651 + to_multiple + 1.5801 winner + -0.1528 format + -2.8401 re_subj(b) Suppose we have an observation where to_multiple=0, winner=1, format=0, and re_subj=0. What is the predicted probability that this message is spam?…

Chapter 9 Solutions

Elementary Statistics Plus MyLab Statistics with Pearson eText -- Access Card Package (7th Edition) (What's New in Statistics)

Ch. 9.1 - A director of alumni affairs at a small college...Ch. 9.1 - A researcher conducts a study to determine whether...Ch. 9.1 - Consider the data on page 469 on the salaries and...Ch. 9.1 - Calculate the correlation coefficient for the...Ch. 9.1 - Use technology to calculate the correlation...Ch. 9.1 - In Try It Yourself 4, you calculated the...Ch. 9.1 - In Try It Yourself 5, you calculated the...Ch. 9.1 - Two variables have a positive linear correlation....Ch. 9.1 - Describe the range of values for the correlation...Ch. 9.1 - What does the sample correlation coefficient r...

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Solution Summary: The author explains how the regression equation for the given data is stackrely=21.0+0.139x.

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