Business Analytics
3rd Edition
ISBN: 9780135231678
Author: Evans, James R. (james Robert)
Publisher: PEARSON EDUCATION (COLLEGE)
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Textbook Question
Chapter 2, Problem 13PE
In the Sales Transactions database, use Excel’s filtering capability to extract
- a. all orders that used PayPal.
- b. all orders under $100.
- c. all orders that were over $100 and used a credit card.
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Students have asked these similar questions
(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 2 Solutions
Business Analytics
Ch. 2 - Explain the difference between a data set and a...Ch. 2 - For the Monthly Product Sales Excel file, use the...Ch. 2 - For the Monthly Product Sales Excel file, use the...Ch. 2 - What does the term filtering mean in the context...Ch. 2 - Convert the Credit Risk database to an Excel...Ch. 2 - Sort the data in the purchase orders database from...Ch. 2 - Prob. 2.4CYUCh. 2 - Prob. 3.1CYUCh. 2 - Prob. 3.2CYUCh. 2 - Prob. 3.3CYU
Ch. 2 - Prob. 4.1CYUCh. 2 - In the Purchase Orders database, what will =...Ch. 2 - Prob. 4.3CYUCh. 2 - Prob. 5.1CYUCh. 2 - Prob. 5.2CYUCh. 2 - Prob. 5.3CYUCh. 2 - Prob. 5.4CYUCh. 2 - Prob. 6.1CYUCh. 2 - Prob. 6.2CYUCh. 2 - Prob. 6.3CYUCh. 2 - The Excel file MBA Motivation and Salary...Ch. 2 - Prob. 2PECh. 2 - The Budget Forecasting database shows estimated...Ch. 2 - Convert the Store and Regional Sales database to...Ch. 2 - Convert the Purchase Orders database to an Excel...Ch. 2 - Prob. 6PECh. 2 - The Excel file Corporate Default Database...Ch. 2 - Open the Excel file Store and Regional Sales...Ch. 2 - In the Excel file Automobile Quality, search for...Ch. 2 - In the Purchase Orders database, conduct a Pareto...Ch. 2 - Conduct a Pareto analysis for the number of...Ch. 2 - Prob. 12PECh. 2 - In the Sales Transactions database, use Excels...Ch. 2 - Filter the data in the Bicycle Inventory database...Ch. 2 - Use the Excel file Credit Risk Data that was...Ch. 2 - Apply the Advanced Filter to the Credit Risk Data...Ch. 2 - Prob. 17PECh. 2 - Prob. 18PECh. 2 - Modify the data in the Base Data worksheet in the...Ch. 2 - Prob. 20PECh. 2 - Figure 2.41 shows the 2016 U.S. federal income tax...Ch. 2 - For the Bicycle Inventory database, write a...Ch. 2 - Prob. 23PECh. 2 - A manager needs to identify some information from...Ch. 2 - The Excel file SP 500 provides open, high, low,...Ch. 2 - Enhance the Sales Transactions database file to...Ch. 2 - Prob. 27PECh. 2 - For this exercise, use the Purchase Orders...Ch. 2 - Use INDEX and MATCH functions to fill in a table...Ch. 2 - Prob. 30PECh. 2 - Prob. 31PECh. 2 - Prob. 32PECh. 2 - Prob. 33PECh. 2 - Prob. 34PECh. 2 - A college graduate who is living in Cincinnati...Ch. 2 - The Excel file Payroll Data provides hourly...Ch. 2 - Construct PivotTables showing the counts of gender...Ch. 2 - Prob. 38PECh. 2 - Prob. 39PECh. 2 - Prob. 40PECh. 2 - Prob. 2.1C
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