EBK BUSINESS STATISTICS
7th Edition
ISBN: 8220102743984
Author: STEPHAN
Publisher: PEARSON
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Chapter 2, Problem 2.85CYU
What are the three different ways to break down the percentages in a
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What were the average sales for the four weeks prior to the experiment?
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What is the mean difference in sales between the experimental and regular POP time periods?
State the null hypothesis being tested by the paired sample t-test.
Do you reject or retain the null hypothesis?
At a 95% significance level, was the difference significant? Explain why or why not using the results from the paired sample t-test.
Should the manager of the retail chain install new digital displays in each store? Justify your answer.
A retail chain is interested in determining whether a digital video point-of-purchase (POP) display would stimulate higher sales for a brand advertised compared to the standard cardboard point-of-purchase display. To test this, a one-shot static group design experiment was conducted over a four-week period in 100 different stores. Fifty stores were randomly assigned to the control treatment (standard display) and the other 50 stores were randomly assigned to the experimental treatment (digital display). Compare the sales of the control group (standard POP) to the experimental group (digital POP).
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List the null hypothesis being tested.
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Question 4
An article in Quality Progress (May 2011, pp. 42-48) describes the use of factorial experiments to improve a
silver powder production process. This product is used in conductive pastes to manufacture a wide variety of
products ranging from silicon wafers to elastic membrane switches. Powder density (g/cm²) and surface area
(cm/g) are the two critical characteristics of this product. The experiments involved three factors: reaction
temperature, ammonium percentage, stirring rate. Each of these factors had two levels, and the design was
replicated twice. The design is shown in Table 3.
A222222222222233
Stir Rate
(RPM)
Ammonium
(%)
Table 3: Silver Powder Experiment from Exercise 13.23
Temperature
(°C)
Density
Surface Area
100
8
14.68
0.40
100
8
15.18
0.43
30
100
8
15.12
0.42
30
100
17.48
0.41
150
7.54
0.69
150
8
6.66
0.67
30
150
8
12.46
0.52
30
150
8
12.62
0.36
100
40
10.95
0.58
100
40
17.68
0.43
30
100
40
12.65
0.57
30
100
40
15.96
0.54
150
40
8.03
0.68
150
40
8.84
0.75
30
150…
Chapter 2 Solutions
EBK BUSINESS STATISTICS
Ch. 2 - Prob. 2.1LBCh. 2 - The following data represent the responses to two...Ch. 2 - Prob. 2.3ACCh. 2 - Prob. 2.4ACCh. 2 - Prob. 2.5ACCh. 2 - Prob. 2.6ACCh. 2 - Prob. 2.7ACCh. 2 - A survey of 1,085 adults asked Do you enjoy...Ch. 2 - Prob. 2.9ACCh. 2 - Prob. 2.10AC
Ch. 2 - Prob. 2.11LBCh. 2 - Prob. 2.12LBCh. 2 - Prob. 2.13LBCh. 2 - Prob. 2.14LBCh. 2 - The file NBACost2013 contains the total cost ($)...Ch. 2 - The file UTILITY contains the following data about...Ch. 2 - Prob. 2.17ACCh. 2 - One operation of a mill to cut pieces of steel...Ch. 2 - A manufacturing company produces steel housings...Ch. 2 - Prob. 2.21ACCh. 2 - Prob. 2.22ACCh. 2 - Prob. 2.23ACCh. 2 - An online survey of CFA Institute members was...Ch. 2 - Prob. 2.25ACCh. 2 - Prob. 2.26ACCh. 2 - Prob. 2.27ACCh. 2 - The following table indicates the percentage of...Ch. 2 - Prob. 2.29ACCh. 2 - Prob. 2.30ACCh. 2 - A study of Kickstarter projects showed that 54.2%...Ch. 2 - Prob. 2.32ACCh. 2 - Prob. 2.33LBCh. 2 - Prob. 2.34LBCh. 2 - Prob. 2.35ACCh. 2 - Prob. 2.37ACCh. 2 - The file UTILITY contains the following data about...Ch. 2 - Prob. 2.39ACCh. 2 - Prob. 2.40ACCh. 2 - Prob. 2.41ACCh. 2 - Prob. 2.42ACCh. 2 - Prob. 2.43ACCh. 2 - Prob. 2.45ACCh. 2 - Prob. 2.46ACCh. 2 - The data stored in DRINK represents the amount of...Ch. 2 - Prob. 2.48LBCh. 2 - Prob. 2.49LBCh. 2 - Prob. 2.50ACCh. 2 - Data were collected on the typical cost of dining...Ch. 2 - College football is big business, with coaches pay...Ch. 2 - Prob. 2.54ACCh. 2 - Prob. 2.56ACCh. 2 - Prob. 2.57ACCh. 2 - Prob. 2.58ACCh. 2 - Prob. 2.59ACCh. 2 - Prob. 2.60ACCh. 2 - Prob. 2.61ACCh. 2 - Prob. 2.66ACCh. 2 - Prob. 2.67ACCh. 2 - Prob. 2.68ACCh. 2 - Prob. 2.69ACCh. 2 - Prob. 2.71ACCh. 2 - (Student Project) The Data and Story Library...Ch. 2 - Prob. 2.73ACCh. 2 - Prob. 2.75ACCh. 2 - Figure 2.1 shows a bar chart and a pie chart for...Ch. 2 - Prob. 2.78ACCh. 2 - Prob. 2.79CYUCh. 2 - Prob. 2.80CYUCh. 2 - Prob. 2.81CYUCh. 2 - Compare and contrast the bar chart for categorical...Ch. 2 - Prob. 2.83CYUCh. 2 - Prob. 2.84CYUCh. 2 - What are the three different ways to break down...Ch. 2 - How can a multidimensional table differ from a...Ch. 2 - Prob. 2.87CYUCh. 2 - Prob. 2.88CRPCh. 2 - The owner of a restaurant that serves...Ch. 2 - Suppose that the owner of the restaurant in...Ch. 2 - Prob. 2.94CRPCh. 2 - One of the major measures of the quality of...Ch. 2 - Prob. 2.98CRPCh. 2 - The file CEO-Compensation includes the total...Ch. 2 - Prob. 2.100CRPCh. 2 - What was the average price of a room at two-star,...Ch. 2 - Prob. 2.102CRPCh. 2 - Prob. 2.103CRPCh. 2 - The following data (stored in Drink) represent...Ch. 2 - Prob. 2.106CRPCh. 2 - Prob. 2.109RWE
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- - + ++ Table 2: Crack Experiment for Exercise 2 A B C D Treatment Combination (1) Replicate I II 7.037 6.376 14.707 15.219 |++++ 1 བྱ॰༤༠སྦྱོ སྦྱོཋཏྟཱུ a b ab 11.635 12.089 17.273 17.815 с ас 10.403 10.151 4.368 4.098 bc abc 9.360 9.253 13.440 12.923 d 8.561 8.951 ad 16.867 17.052 bd 13.876 13.658 abd 19.824 19.639 cd 11.846 12.337 acd 6.125 5.904 bcd 11.190 10.935 abcd 15.653 15.053 Question 3 Continuation of Exercise 2. One of the variables in the experiment described in Exercise 2, heat treatment method (C), is a categorical variable. Assume that the remaining factors are continuous. (a) Write two regression models for predicting crack length, one for each level of the heat treatment method variable. What differences, if any, do you notice in these two equations? (b) Generate appropriate response surface contour plots for the two regression models in part (a). (c) What set of conditions would you recommend for the factors A, B, and D if you use heat treatment method C = +? (d) Repeat…arrow_forwardQuestion 2 A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content (B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The data are shown in Table 2. 1 (a) Estimate the factor effects. Which factor effects appear to be large? (b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05. (c) Write down a regression model that can be used to predict crack length as a function of the significant main effects and interactions you have identified in part (b). (d) Analyze the residuals from this experiment. (e) Is there an…arrow_forwardA 24-1 design has been used to investigate the effect of four factors on the resistivity of a silicon wafer. The data from this experiment are shown in Table 4. Table 4: Resistivity Experiment for Exercise 5 Run A B с D Resistivity 1 23 2 3 4 5 6 7 8 9 10 11 12 I+I+I+I+Oooo 0 0 ||++TI++o000 33.2 4.6 31.2 9.6 40.6 162.4 39.4 158.6 63.4 62.6 58.7 0 0 60.9 3 (a) Estimate the factor effects. Plot the effect estimates on a normal probability scale. (b) Identify a tentative model for this process. Fit the model and test for curvature. (c) Plot the residuals from the model in part (b) versus the predicted resistivity. Is there any indication on this plot of model inadequacy? (d) Construct a normal probability plot of the residuals. Is there any reason to doubt the validity of the normality assumption?arrow_forward
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