Elementary Statistics (Text Only)
2nd Edition
ISBN: 9780077836351
Author: Author
Publisher: McGraw Hill
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Chapter 14.1, Problem 14E
In a one-way ANOVA, the following data were collected: SSTr = 145.34, SSE = 35.45, N = 9, I = 3.
- How many samples are there?
- How many degrees of freedom are there for SSTr and SSE?
- Compute the
mean squares MSTr and MSE. - Compute the value of the test statistic F.
- Can you conclude that two or more of the population means are different? Use the
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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 14 Solutions
Elementary Statistics (Text Only)
Ch. 14.1 - In Exercises 7 and 8, fill in each blank with the...Ch. 14.1 - Prob. 8ECh. 14.1 - Prob. 9ECh. 14.1 - Prob. 10ECh. 14.1 - Prob. 11ECh. 14.1 - Prob. 12ECh. 14.1 - In a one-way ANOVA, the following data were...Ch. 14.1 - In a one-way ANOVA, the following data were...Ch. 14.1 - Samples were drawn from three populations. The...Ch. 14.1 - Samples were drawn from three populations. The...
Ch. 14.1 - Pesticide danger: One of the factors that...Ch. 14.1 - Life-saving drug: Penicillin is produced by the...Ch. 14.1 - Pesticide danger: Using the data in Exercise 17,...Ch. 14.1 - Life-saving drug: Using the data in Exercise 18,...Ch. 14.1 - Artificial hips: Artificial hip joints consist of...Ch. 14.1 - Floods: Rapid drainage of floodwater is crucial to...Ch. 14.1 - Artificial hips: Using the data in Exercise 21,...Ch. 14.1 - Floods: Using the data in Exercise 22, perform the...Ch. 14.1 - Polluting power plants: Power plants can emit...Ch. 14.1 - Prob. 26ECh. 14.1 - Prob. 27ECh. 14.1 - Prob. 28ECh. 14.1 - Prob. 29ECh. 14.1 - Prob. 30ECh. 14.1 - Prob. 31ECh. 14.2 - Prob. 5ECh. 14.2 - Prob. 6ECh. 14.2 - Prob. 7ECh. 14.2 - Prob. 8ECh. 14.2 - In a two-way ANOVA, the P-value for interactions...Ch. 14.2 - Prob. 10ECh. 14.2 - Prob. 11ECh. 14.2 - Prob. 12ECh. 14.2 - Prob. 13ECh. 14.2 - Prob. 14ECh. 14.2 - Prob. 15ECh. 14.2 - Prob. 16ECh. 14.2 - Prob. 17ECh. 14.2 - Prob. 18ECh. 14.2 - Prob. 19ECh. 14.2 - Prob. 20ECh. 14.2 - Prob. 21ECh. 14.2 - Prob. 22ECh. 14.2 - Prob. 23ECh. 14.2 - Strong beams: The following table presents...Ch. 14.2 - Prob. 25ECh. 14.2 - Prob. 26ECh. 14.2 - Fruit yields: An agricultural scientist performed...Ch. 14.2 - Prob. 28ECh. 14.2 - Prob. 29ECh. 14 - Exercises 1-4 refer to the following data: At a...Ch. 14 - Prob. 2CQCh. 14 - Prob. 3CQCh. 14 - Prob. 4CQCh. 14 - Prob. 5CQCh. 14 - Prob. 6CQCh. 14 - Prob. 7CQCh. 14 - Prob. 8CQCh. 14 - Prob. 9CQCh. 14 - Prob. 10CQCh. 14 - Prob. 1RECh. 14 - Prob. 2RECh. 14 - Prob. 3RECh. 14 - Prob. 4RECh. 14 - Prob. 5RECh. 14 - Prob. 6RECh. 14 - Prob. 7RECh. 14 - Prob. 8RECh. 14 - Prob. 9RECh. 14 - Prob. 10RECh. 14 - Prob. 11RECh. 14 - Prob. 12RECh. 14 - Prob. 13RECh. 14 - Prob. 14RECh. 14 - Prob. 15RECh. 14 - Prob. 1WAICh. 14 - Prob. 2WAICh. 14 - Prob. 3WAICh. 14 - Prob. 4WAICh. 14 - Prob. 5WAICh. 14 - Prob. 1CSCh. 14 - Prob. 2CSCh. 14 - Prob. 3CSCh. 14 - Prob. 4CS
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