Business Analytics, Loose-leaf Edition (3rd Edition)
3rd Edition
ISBN: 9780135231692
Author: James R. Evans
Publisher: PEARSON
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Chapter 5, Problem 27PE
The Excel file Call Center Data shows that in a sample of
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A major company in the Montreal area, offering a range of engineering services from project preparation to construction execution, and industrial project management, wants to ensure that the individuals who are responsible for project cost estimation and bid preparation demonstrate a certain uniformity in their estimates. The head of civil engineering and municipal services decided to structure an experimental plan to detect if there could be significant differences in project evaluation.
Seven projects were selected, each of which had to be evaluated by each of the two estimators, with the order of the projects submitted being random. The obtained estimates are presented in the table below.
a) Complete the table above by calculating: i. The differences (A-B) ii. The sum of the differences iii. The mean of the differences iv. The standard deviation of the differences
b) What is the value of the t-statistic?
c) What is the critical t-value for this test at a significance level of 1%?…
Compute the relative risk of falling for the two groups (did not stop walking vs. did stop). State/interpret your result verbally.
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Chapter 5 Solutions
Business Analytics, Loose-leaf Edition (3rd Edition)
Ch. 5 - Lauren drinks a variety of soft drinks. Over the...Ch. 5 - A home improvement company in Cincinnati ran a...Ch. 5 - Consider the experiment of drawing two cards...Ch. 5 - Three coins are drop on a table. List all possible...Ch. 5 - A market research company surveyed consumers to...Ch. 5 - Refer to the card scenario described in Problem 3....Ch. 5 - Refer to the coin scenario described in Problem 4....Ch. 5 - Prob. 8PECh. 5 - Prob. 9PECh. 5 - An airline tracks data on its flight arrivals....
Ch. 5 - A survey of 200 college graduates who have been...Ch. 5 - Prob. 12PECh. 5 - A survey of shopping habits found the percentage...Ch. 5 - A Canadian business school summarized the gender...Ch. 5 - Prob. 15PECh. 5 - Use the Civilian Labor Force data in the Excel...Ch. 5 - Prob. 17PECh. 5 - A home pregnancy test is not always accurate....Ch. 5 - In the scenario in Problem 3, what is the...Ch. 5 - In the roulette example described in Problem 8,...Ch. 5 - Prob. 21PECh. 5 - An investor estimates that there is a 1in10 chance...Ch. 5 - The weekly demand of a slow-moving product has the...Ch. 5 - Construct the probability distribution for the...Ch. 5 - Based on the data in the Excel file Consumer...Ch. 5 - A major application of analytics in marketing is...Ch. 5 - The Excel file Call Center Data shows that in a...Ch. 5 - If a cell phone company conducted a telemarketing...Ch. 5 - During one year, a particular mutual fund...Ch. 5 - A popular resort hotel has 300 rooms and is...Ch. 5 - A telephone call center where people place...Ch. 5 - A financial consultant has an average of eight...Ch. 5 - The number and frequency of Atlantic hurricanes...Ch. 5 - Prob. 34PECh. 5 - Prob. 35PECh. 5 - Prob. 36PECh. 5 - In determining automobile mileage ratings, it was...Ch. 5 - The distribution of SAT scores in math for an...Ch. 5 - A popular soft drink is sold in 2-liter...Ch. 5 - A supplier contract calls for a key dimension of a...Ch. 5 - Historical data show that customers who download...Ch. 5 - A lightbulb is warranted to last for 5,000 hours....Ch. 5 - The actual delivery time from Giodannis Pizza is...Ch. 5 - Apply the chi-square goodness of fit test to the...Ch. 5 - Apply the chi-square goodness of fit test to the...Ch. 5 - Compute the daily change of the closing price for...
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- Question 1 The data shown in Table 1 are and R values for 24 samples of size n = 5 taken from a process producing bearings. The measurements are made on the inside diameter of the bearing, with only the last three decimals recorded (i.e., 34.5 should be 0.50345). Table 1: Bearing Diameter Data Sample Number I R Sample Number I R 1 34.5 3 13 35.4 8 2 34.2 4 14 34.0 6 3 31.6 4 15 37.1 5 4 31.5 4 16 34.9 7 5 35.0 5 17 33.5 4 6 34.1 6 18 31.7 3 7 32.6 4 19 34.0 8 8 33.8 3 20 35.1 9 34.8 7 21 33.7 2 10 33.6 8 22 32.8 1 11 31.9 3 23 33.5 3 12 38.6 9 24 34.2 2 (a) Set up and R charts on this process. Does the process seem to be in statistical control? If necessary, revise the trial control limits. [15 pts] (b) If specifications on this diameter are 0.5030±0.0010, find the percentage of nonconforming bearings pro- duced by this process. Assume that diameter is normally distributed. [10 pts] 1arrow_forward4. (5 pts) Conduct a chi-square contingency test (test of independence) to assess whether there is an association between the behavior of the elderly person (did not stop to talk, did stop to talk) and their likelihood of falling. Below, please state your null and alternative hypotheses, calculate your expected values and write them in the table, compute the test statistic, test the null by comparing your test statistic to the critical value in Table A (p. 713-714) of your textbook and/or estimating the P-value, and provide your conclusions in written form. Make sure to show your work. Did not stop walking to talk Stopped walking to talk Suffered a fall 12 11 Totals 23 Did not suffer a fall | 2 Totals 35 37 14 46 60 Tarrow_forwardQuestion 2 Parts manufactured by an injection molding process are subjected to a compressive strength test. Twenty samples of five parts each are collected, and the compressive strengths (in psi) are shown in Table 2. Table 2: Strength Data for Question 2 Sample Number x1 x2 23 x4 x5 R 1 83.0 2 88.6 78.3 78.8 3 85.7 75.8 84.3 81.2 78.7 75.7 77.0 71.0 84.2 81.0 79.1 7.3 80.2 17.6 75.2 80.4 10.4 4 80.8 74.4 82.5 74.1 75.7 77.5 8.4 5 83.4 78.4 82.6 78.2 78.9 80.3 5.2 File Preview 6 75.3 79.9 87.3 89.7 81.8 82.8 14.5 7 74.5 78.0 80.8 73.4 79.7 77.3 7.4 8 79.2 84.4 81.5 86.0 74.5 81.1 11.4 9 80.5 86.2 76.2 64.1 80.2 81.4 9.9 10 75.7 75.2 71.1 82.1 74.3 75.7 10.9 11 80.0 81.5 78.4 73.8 78.1 78.4 7.7 12 80.6 81.8 79.3 73.8 81.7 79.4 8.0 13 82.7 81.3 79.1 82.0 79.5 80.9 3.6 14 79.2 74.9 78.6 77.7 75.3 77.1 4.3 15 85.5 82.1 82.8 73.4 71.7 79.1 13.8 16 78.8 79.6 80.2 79.1 80.8 79.7 2.0 17 82.1 78.2 18 84.5 76.9 75.5 83.5 81.2 19 79.0 77.8 20 84.5 73.1 78.2 82.1 79.2 81.1 7.6 81.2 84.4 81.6 80.8…arrow_forward
- Name: Lab Time: Quiz 7 & 8 (Take Home) - due Wednesday, Feb. 26 Contingency Analysis (Ch. 9) In lab 5, part 3, you will create a mosaic plot and conducted a chi-square contingency test to evaluate whether elderly patients who did not stop walking to talk (vs. those who did stop) were more likely to suffer a fall in the next six months. I have tabulated the data below. Answer the questions below. Please show your calculations on this or a separate sheet. Did not stop walking to talk Stopped walking to talk Totals Suffered a fall Did not suffer a fall Totals 12 11 23 2 35 37 14 14 46 60 Quiz 7: 1. (2 pts) Compute the odds of falling for each group. Compute the odds ratio for those who did not stop walking vs. those who did stop walking. Interpret your result verbally.arrow_forwardSolve please and thank you!arrow_forward7. In a 2011 article, M. Radelet and G. Pierce reported a logistic prediction equation for the death penalty verdicts in North Carolina. Let Y denote whether a subject convicted of murder received the death penalty (1=yes), for the defendant's race h (h1, black; h = 2, white), victim's race i (i = 1, black; i = 2, white), and number of additional factors j (j = 0, 1, 2). For the model logit[P(Y = 1)] = a + ß₁₂ + By + B²², they reported = -5.26, D â BD = 0, BD = 0.17, BY = 0, BY = 0.91, B = 0, B = 2.02, B = 3.98. (a) Estimate the probability of receiving the death penalty for the group most likely to receive it. [4 pts] (b) If, instead, parameters used constraints 3D = BY = 35 = 0, report the esti- mates. [3 pts] h (c) If, instead, parameters used constraints Σ₁ = Σ₁ BY = Σ; B = 0, report the estimates. [3 pts] Hint the probabilities, odds and odds ratios do not change with constraints.arrow_forward
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