Applied Statistics in Business and Economics
5th Edition
ISBN: 9780077837303
Author: David Doane, Lori Seward Senior Instructor of Operations Management
Publisher: McGraw-Hill Education
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Chapter 13.3, Problem 9SE
Observations are taken on net revenue from sales of a certain LCD TV at 50 retail outlets. The regression model was Y = net revenue (thousands of dollars), X1 = shipping cost (dollars per unit), X2 = expenditures on print advertising (thousands of dollars), X3 = expenditure on electronic media ads (thousands), X4 = rebate rate (percent of retail price). (a) Calculate the t statistic for each coefficient to test for β = 0. (b) Look up the critical value of Student’s t in Appendix D for a two-tailed test at α = .01. Which coefficients differ significantly from zero? (c) Use Excel to find the p-value for each coefficient.
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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 13 Solutions
Applied Statistics in Business and Economics
Ch. 13.1 - Observations are taken on net revenue from sales...Ch. 13.1 - Observations are taken on sales of a certain...Ch. 13.1 - Prob. 3SECh. 13.1 - A regression model to predict Y, the...Ch. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.2 - Prob. 7SECh. 13.2 - Refer to the ANOVA table below. (a) State the...Ch. 13.3 - Observations are taken on net revenue from sales...Ch. 13.3 - Observations are taken on sales of a certain...
Ch. 13.3 - Prob. 11SECh. 13.3 - A regression model to predict Y, the state...Ch. 13.4 - A regression of accountants starting salaries in a...Ch. 13.4 - An agribusiness performed a regression of wheat...Ch. 13.5 - Prob. 15SECh. 13.5 - A regression model to predict the price of...Ch. 13.5 - Prob. 17SECh. 13.5 - Prob. 18SECh. 13.6 - Prob. 19SECh. 13.6 - Prob. 20SECh. 13.7 - Prob. 21SECh. 13.7 - Using the Metals data, construct a correlation...Ch. 13.8 - Prob. 23SECh. 13.8 - Which violations of regression assumptions, if...Ch. 13 - (a) List two limitations of simple regression. (b)...Ch. 13 - (a) What does represent in the regression model?...Ch. 13 - Prob. 3CRCh. 13 - Prob. 4CRCh. 13 - Prob. 5CRCh. 13 - Prob. 6CRCh. 13 - Prob. 7CRCh. 13 - Prob. 8CRCh. 13 - Prob. 9CRCh. 13 - (a) State the formula for the standard error of...Ch. 13 - (a) What is a categorical predictor? (b) Why is a...Ch. 13 - Prob. 12CRCh. 13 - Prob. 13CRCh. 13 - (a) What is multicollinearity? (b) What are its...Ch. 13 - Prob. 15CRCh. 13 - (a) State the formula for a variance inflation...Ch. 13 - Prob. 17CRCh. 13 - Prob. 18CRCh. 13 - Prob. 19CRCh. 13 - Prob. 20CRCh. 13 - (a) Name two ways to detect autocorrelated...Ch. 13 - (a) What is a lurking variable? How might it be...Ch. 13 - Instructions for Data Sets: Choose one of the data...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 27CECh. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 30CECh. 13 - Prob. 31CECh. 13 - Prob. 32CECh. 13 - Prob. 33CECh. 13 - Prob. 34CECh. 13 - Prob. 35CECh. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Note: Exercises marked are based on optional...Ch. 13 - Prob. 39CECh. 13 - Prob. 40CECh. 13 - Prob. 41CECh. 13 - In a model of Fords quarterly revenue TotalRevenue...Ch. 13 - In a study of paint peel problems, a regression...Ch. 13 - A hospital emergency room analyzed n = 17,664...Ch. 13 - Prob. 45CECh. 13 - A researcher used stepwise regression to create...Ch. 13 - A sports enthusiast created an equation to predict...Ch. 13 - An expert witness in a case of alleged racial...Ch. 13 - Prob. 50CECh. 13 - Prob. 51CECh. 13 - Prob. 52CECh. 13 - Which statement is correct concerning one-factor...Ch. 13 - Prob. 2ERQCh. 13 - Prob. 3ERQCh. 13 - Prob. 4ERQCh. 13 - Prob. 5ERQCh. 13 - Prob. 6ERQCh. 13 - Prob. 7ERQCh. 13 - Prob. 8ERQCh. 13 - Prob. 9ERQCh. 13 - Prob. 10ERQCh. 13 - Prob. 11ERQCh. 13 - Prob. 12ERQCh. 13 - Prob. 13ERQCh. 13 - Prob. 14ERQCh. 13 - Prob. 15ERQ
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