Gen Combo Ll Applied Statistics In Business & Economics; Connect Access Card
6th Edition
ISBN: 9781260260632
Author: David Doane, Lori Seward Senior Instructor of Operations Management
Publisher: McGraw-Hill Education
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Chapter 12.7, Problem 33SE
a.
To determine
Find the confidence interval and the prediction intervals for Y using MegaStat or MINITAB.
b.
To determine
Write the 95% confidence interval and the prediction interval for x = 15.
c.
To determine
Find the 95% confidence interval for
d.
To determine
Compare the result from the part (c) and part (b). Explain how the two intervals differ.
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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 12 Solutions
Gen Combo Ll Applied Statistics In Business & Economics; Connect Access Card
Ch. 12.1 - For each sample, do a test for zero correlation....Ch. 12.1 - Instructions for Exercises 12.2 and 12.3: (a) Make...Ch. 12.1 - Prob. 3SECh. 12.1 - Prob. 4SECh. 12.1 - Instructions for exercises 12.412.6: (a) Make a...Ch. 12.1 - Prob. 6SECh. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.2 - Prob. 9SECh. 12.2 - (a) Interpret the slope of the fitted regression...
Ch. 12.2 - (a) Interpret the slope of the fitted regression...Ch. 12.3 - Prob. 12SECh. 12.3 - Prob. 13SECh. 12.3 - The regression equation Credits = 15.4 .07 Work...Ch. 12.3 - Below are fitted regressions for Y = asking price...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.3 - Refer back to the regression equation in exercise...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.18 and 12.19: (a)...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.4 - Instructions for exercises 12.2012.22: (a) Use...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - Instructions for exercises 12.23 and 12.24: (a)...Ch. 12.5 - A regression was performed using data on 32 NFL...Ch. 12.5 - A regression was performed using data on 16...Ch. 12.6 - Below is a regression using X = home price (000),...Ch. 12.6 - Below is a regression using X = average price, Y =...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.6 - Instructions for exercises 12.2912.31: (a) Use...Ch. 12.7 - Refer to the Weekly Earnings data set below. (a)...Ch. 12.7 - Prob. 33SECh. 12.8 - Prob. 34SECh. 12.8 - Prob. 35SECh. 12.9 - Calculate the standardized residual ei and...Ch. 12.9 - Prob. 37SECh. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - An estimated regression for a random sample of...Ch. 12.9 - Prob. 40SECh. 12.9 - Prob. 41SECh. 12.9 - Prob. 42SECh. 12.9 - Prob. 43SECh. 12.11 - Prob. 44SECh. 12.11 - Prob. 45SECh. 12 - (a) How does correlation analysis differ from...Ch. 12 - (a) What is a simple regression model? (b) State...Ch. 12 - (a) Explain how you fit a regression to an Excel...Ch. 12 - (a) Explain the logic of the ordinary least...Ch. 12 - (a) Why cant we use the sum of the residuals to...Ch. 12 - Prob. 6CRCh. 12 - Prob. 7CRCh. 12 - Prob. 8CRCh. 12 - Prob. 9CRCh. 12 - Prob. 10CRCh. 12 - Prob. 11CRCh. 12 - Prob. 12CRCh. 12 - (a) What is heteroscedasticity? Identify its two...Ch. 12 - (a) What is autocorrelation? Identify two main...Ch. 12 - Prob. 15CRCh. 12 - Prob. 16CRCh. 12 - (a) What is a log transform? (b) What are its...Ch. 12 - (a) When is logistic regression needed? (b) Why...Ch. 12 - Prob. 46CECh. 12 - Prob. 47CECh. 12 - Prob. 48CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 50CECh. 12 - Prob. 51CECh. 12 - Prob. 52CECh. 12 - Prob. 53CECh. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Instructions: Choose one or more of the data sets...Ch. 12 - Prob. 57CECh. 12 - Prob. 58CECh. 12 - Prob. 59CECh. 12 - Prob. 60CECh. 12 - Prob. 61CECh. 12 - Prob. 62CECh. 12 - Prob. 63CECh. 12 - Prob. 64CECh. 12 - Prob. 65CECh. 12 - In the following regression, X = weekly pay, Y =...Ch. 12 - Prob. 67CECh. 12 - In the following regression, X = total assets (...Ch. 12 - Prob. 69CECh. 12 - Below are percentages for annual sales growth and...Ch. 12 - Prob. 71CECh. 12 - Prob. 72CECh. 12 - Prob. 73CECh. 12 - Simple regression was employed to establish the...Ch. 12 - Prob. 75CECh. 12 - Prob. 76CECh. 12 - Prob. 77CECh. 12 - Below are revenue and profit (both in billions)...Ch. 12 - Below are fitted regressions based on used vehicle...Ch. 12 - Below are results of a regression of Y = average...Ch. 12 - Prob. 81CE
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