BASIC PRACTICE OF STATS-LL W/SAPLINGPLU
8th Edition
ISBN: 9781319216245
Author: Moore
Publisher: MAC HIGHER
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Chapter 26, Problem 26.32E
(a)
To determine
To check: Whether there is significant evidence that people with higher NEA increase gain less fat or not.
(b)
To determine
To find: The 90% confidence interval for the slope of the population regression line.
(c)
To determine
To find: The 95% prediction interval for the Sam’s NEA increased by 400 calories.
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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)
Business discuss
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 26 Solutions
BASIC PRACTICE OF STATS-LL W/SAPLINGPLU
Ch. 26.2 - Prob. 1AYKCh. 26.3 - Prob. 2AYKCh. 26.3 - Prob. 3AYKCh. 26.4 - Prob. 4AYKCh. 26.4 - Prob. 5AYKCh. 26.4 - Prob. 6AYKCh. 26.5 - Prob. 7AYKCh. 26.5 - Prob. 8AYKCh. 26.6 - Prob. 9AYKCh. 26.6 - Prob. 10AYK
Ch. 26.6 - Prob. 11AYKCh. 26.7 - Prob. 12AYKCh. 26.7 - Prob. 13AYKCh. 26.8 - Prob. 14AYKCh. 26.8 - Prob. 15AYKCh. 26 - Prob. 26.16CYSCh. 26 - Prob. 26.17CYSCh. 26 - Prob. 26.18CYSCh. 26 - Prob. 26.19CYSCh. 26 - Prob. 26.20CYSCh. 26 - Prob. 26.21CYSCh. 26 - Prob. 26.22CYSCh. 26 - Prob. 26.23CYSCh. 26 - Prob. 26.24CYSCh. 26 - Prob. 26.25ECh. 26 - Prob. 26.26ECh. 26 - Prob. 26.27ECh. 26 - Prob. 26.28ECh. 26 - Prob. 26.29ECh. 26 - Prob. 26.30ECh. 26 - Prob. 26.31ECh. 26 - Prob. 26.32ECh. 26 - Prob. 26.33ECh. 26 - Prob. 26.34ECh. 26 - Prob. 26.35ECh. 26 - Prob. 26.36ECh. 26 - Prob. 26.37ECh. 26 - Prob. 26.38ECh. 26 - Prob. 26.40ECh. 26 - Prob. 26.41ECh. 26 - Prob. 26.42ECh. 26 - Prob. 26.43ECh. 26 - Prob. 26.46ECh. 26 - Prob. 26.47ECh. 26 - Prob. 26.48ECh. 26 - Prob. 26.49E
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