Essentials Of Statistics For Business & Economics
9th Edition
ISBN: 9780357045435
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
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Chapter 8.2, Problem 15E
Sales personnel for Skillings Distributors submit weekly reports listing the customer contacts made during the week. A sample of 65 weekly reports showed a sample
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A marketing professor has surveyed the students at her university to better understand attitudes towards PPT usage for higher education. To be able to make inferences to the entire student body, the sample drawn needs to represent the university’s student population on all key characteristics. The table below shows the five key student demographic variables. The professor found the breakdown of the overall student body in the university’s fact book posted online.
A non-parametric chi-square test was used to test the sample demographics against the population percentages shown in the table above. Review the output for the five chi-square tests on the following pages and answer the five questions:
Based on the chi-square test, which sample variables adequately represent the university’s student population and which ones do not? Support your answer by providing the p-value of the chi-square test and explaining what it means.
Using the results from Question 1, make recommendation for…
A marketing professor has surveyed the students at her university to better understand attitudes towards PPT usage for higher education. To be able to make inferences to the entire student body, the sample drawn needs to represent the university’s student population on all key characteristics. The table below shows the five key student demographic variables. The professor found the breakdown of the overall student body in the university’s fact book posted online.
A non-parametric chi-square test was used to test the sample demographics against the population percentages shown in the table above. Review the output for the five chi-square tests on the following pages and answer the five questions:
Based on the chi-square test, which sample variables adequately represent the university’s student population and which ones do not? Support your answer by providing the p-value of the chi-square test and explaining what it means.
Using the results from Question 1, make recommendation for…
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).
What were the average sales for the standard POP display (control group)?
What were the sales for the digital display (experimental group)?
What is the (mean) difference in sales between the experimental group and control group?
List the null hypothesis being tested.
Do you reject or retain the null hypothesis based on the results of the independent t-test?
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Chapter 8 Solutions
Essentials Of Statistics For Business & Economics
Ch. 8.1 - A simple random sample of 40 items resulted in a...Ch. 8.1 - 2. A simple random sample of 50 items from a...Ch. 8.1 - A simple random sample of 60 items resulted in a...Ch. 8.1 - 4. A 95% confidence interval for a population mean...Ch. 8.1 - Data were collected on the amount spent by 64...Ch. 8.1 - Travel Taxes. In an attempt to assess total daily...Ch. 8.1 - Cost of Dog Ownership. Money reports that the...Ch. 8.1 - Studies show that massage therapy has a variety of...Ch. 8.1 - Cost to Repair Fire Damage. The mean cost to...Ch. 8.1 - 10. Costs are rising for all kinds of medical...
Ch. 8.2 - For a t distribution with 16 degrees of freedom,...Ch. 8.2 - Find the t value(s) for each of the following...Ch. 8.2 - The following sample data are from a normal...Ch. 8.2 - A simple random sample with n = 54 provided a...Ch. 8.2 - 15. Sales personnel for Skillings Distributors...Ch. 8.2 - Years to Bond Maturity. A sample containing years...Ch. 8.2 - Quality Ratings of Airports. The International Air...Ch. 8.2 - Unemployment in Older Workers. Older people often...Ch. 8.2 - Meal Cost in Hong Kong. The mean cost of a meal...Ch. 8.2 - Automobile Insurance Premiums. The average annual...Ch. 8.2 - Telemedicine. Health insurers are beginning to...Ch. 8.2 - Movie Ticket Sales. Marvel Studios motion picture...Ch. 8.3 - 23. How large a sample should be selected to...Ch. 8.3 - The range for a set of data is estimated to be 36....Ch. 8.3 - Refer to the Scheer Industries example in Section...Ch. 8.3 - Gasoline Prices. The U.S. Energy Information...Ch. 8.3 - Salaries of Business Graduates. Annual starting...Ch. 8.3 - 28. Many medical professionals believe that eating...Ch. 8.3 - 29. Customers arrive at a movie theater at the...Ch. 8.3 - Prob. 30ECh. 8.4 - A simple random sample of 400 individuals provides...Ch. 8.4 - A simple random sample of 800 elements generates a...Ch. 8.4 - In a survey, the planning value for the population...Ch. 8.4 - At 95% confidence, how large a sample should be...Ch. 8.4 - Health-Care Survey. In the spring of 2017, the...Ch. 8.4 - According to statistics reported on CNBC, a...Ch. 8.4 - Voter Sentiment. One of the questions Rasmussen...Ch. 8.4 - 38. According to Franchise business review, over...Ch. 8.4 - In 16% of all homes with a stay-at-home parent,...Ch. 8.4 - Prob. 40ECh. 8.4 - Driver’s License Rates. Fewer young people are...Ch. 8.4 - 42. A poll for the presidential campaign sampled...Ch. 8.4 - 43. The Pew Research Center Internet Project,...Ch. 8.5 - Federal Tax Return Errors. Suppose a sample of...Ch. 8.5 - Federal Government Employee Sick Hours. According...Ch. 8.5 - Web Browser Satisfaction. Internet users were...Ch. 8.5 - Speeding Drivers. In 2017, ABC News reported that...Ch. 8 - 44. A sample survey of 54 discount brokers showed...Ch. 8 - 45. A survey conducted by the American Automobile...Ch. 8 - 46. The 92 million Americans of age 50 and over...Ch. 8 - Healthy Sleep Duration. The Centers for Disease...Ch. 8 - The Health Care Cost Institute tracks health care...Ch. 8 - Obesity. Obesity is a risk factor for many health...Ch. 8 - Prob. 54SECh. 8 - 51. In developing patient appointment schedules, a...Ch. 8 - Prob. 56SECh. 8 - 53. The National Center for Education Statistics...Ch. 8 - A USA Today/CNN/Gallup survey of 369 working...Ch. 8 - Social Media Usage. The Pew Research Center has...Ch. 8 - Prob. 60SECh. 8 - The Centers for Disease Control reported the...Ch. 8 - A well-known bank credit card firm wishes to...Ch. 8 - Credit Card Ownership. Credit card ownership...Ch. 8 - 60. Although airline schedules and cost are...Ch. 8 - Driving Speeds. Huston Systems Private Limited...Ch. 8 - Prob. 66SECh. 8 - Prob. 67SECh. 8 - Prob. 68SECh. 8 - Young Professional Magazine Young Professional...Ch. 8 - Gulf Real Estate Properties Gulf Real Estate...Ch. 8 - Metropolitan Research, Inc.
Metropolitan Research,...
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- What were the average sales for the four weeks prior to the experiment? What were the sales during the four weeks when the stores used the digital display? 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.arrow_forwardA 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). What were the average sales for the standard POP display (control group)? What were the sales for the digital display (experimental group)? What is the (mean) difference in sales between the experimental group and control group? List the null hypothesis being tested. Do you reject or retain the null hypothesis based on the results of the independent t-test? Was the difference between the…arrow_forwardQuestion 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…arrow_forward
- - + ++ 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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