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Chapter 9.1, Problem 12P
To determine

Explain what correlation of 0.80 determines about the relationship between times spent on the two activities.

Explain whether person who spends more time on Twitter also spends more time on a social networking site or not.

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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

Bundle: Understandable Statistics, Loose-leaf Version, 12th + WebAssign Printed Access Card for Brase/Brase's Understandable Statistics: Concepts and Methods, 12th Edition, Single-Term

Ch. 9.1 - Prob. 11PCh. 9.1 - Prob. 12PCh. 9.1 - Prob. 13PCh. 9.1 - Health Insurance: Administrative Cost The...Ch. 9.1 - Prob. 15PCh. 9.1 - Geology: Earthquakes Is the magnitude of an...Ch. 9.1 - Prob. 17PCh. 9.1 - Prob. 18PCh. 9.1 - Prob. 19PCh. 9.1 - Prob. 20PCh. 9.1 - Prob. 21PCh. 9.1 - Prob. 22PCh. 9.1 - Prob. 23PCh. 9.1 - Prob. 24PCh. 9.2 - Statistical Literacy In the least-squares line...Ch. 9.2 - Prob. 2PCh. 9.2 - Critical Thinking When we use a least-squares line...Ch. 9.2 - Prob. 4PCh. 9.2 - Prob. 5PCh. 9.2 - Critical Thinking: Interpreting Computer Printouts...Ch. 9.2 - Prob. 7PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 9PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 11PCh. 9.2 - Prob. 12PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 14PCh. 9.2 - Prob. 15PCh. 9.2 - For Problems 718, please do the following. (a)...Ch. 9.2 - Prob. 17PCh. 9.2 - Prob. 18PCh. 9.2 - Prob. 19PCh. 9.2 - Residual Plot: Miles per Gallon Consider the data...Ch. 9.2 - Prob. 21PCh. 9.2 - Prob. 22PCh. 9.2 - Prob. 23PCh. 9.2 - Prob. 24PCh. 9.2 - Prob. 25PCh. 9.3 - Prob. 1PCh. 9.3 - Prob. 2PCh. 9.3 - Prob. 3PCh. 9.3 - Prob. 4PCh. 9.3 - Prob. 5PCh. 9.3 - Prob. 6PCh. 9.3 - Prob. 7PCh. 9.3 - In Problems 712, parts (a) and (b) relate to...Ch. 9.3 - Prob. 9PCh. 9.3 - Prob. 10PCh. 9.3 - In Problems 712, parts (a) and (b) relate to...Ch. 9.3 - Prob. 12PCh. 9.3 - Prob. 13PCh. 9.3 - Prob. 14PCh. 9.3 - Prob. 15PCh. 9.3 - Expand Your Knowledge: Time Series and Serial...Ch. 9.3 - Prob. 17PCh. 9.4 - Statistical Literacy Given the linear regression...Ch. 9.4 - Prob. 2PCh. 9.4 - For Problems 3-6, use appropriate multiple...Ch. 9.4 - For Problems 3-6, use appropriate multiple...Ch. 9.4 - Prob. 5PCh. 9.4 - Prob. 6PCh. 9 - Prob. 1CRPCh. 9 - Prob. 2CRPCh. 9 - Prob. 3CRPCh. 9 - Prob. 4CRPCh. 9 - Prob. 5CRPCh. 9 - Prob. 6CRPCh. 9 - Prob. 7CRPCh. 9 - Prob. 8CRPCh. 9 - Prob. 9CRPCh. 9 - Prob. 10CRPCh. 9 - Prob. 1DHCh. 9 - Prob. 1LCCh. 9 - Prob. 1UTCh. 9 - Prob. 2UTCh. 9 - Prob. 3UTCh. 9 - Prob. 4UTCh. 9 - Prob. 5UTCh. 9 - Prob. 6UTCh. 9 - Prob. 7UTCh. 9 - In Problems 16, please use the following steps (i)...Ch. 9 - Prob. 2CURPCh. 9 - Prob. 3CURPCh. 9 - Prob. 4CURPCh. 9 - Prob. 5CURPCh. 9 - Prob. 6CURPCh. 9 - Prob. 8CURPCh. 9 - Linear Regression: Blood Glucose Let x be a random...
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