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Business Analytics 2nd Global Edition James R. Evans - Solutions
Engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs. Can you determine whether one of the proposed processes is better than the current process?
What would be a confidence interval for an additional sample of mower test performance as in the worksheet Mower Test?
For the data in the worksheet Blade Weight, what is the sampling distribution of the mean, the overall mean, and the standard error of the mean? Is a normal distribution an appropriate assumption for the sampling distribution of the mean?
How many blade weights must be measured to find a 95% confidence interval for the mean blade weight with a sampling error of at most 0.2? What if the sampling error is specified as 0.1?
Explain the difference between the null and alternative hypotheses.
List the steps in the hypothesis-testing procedure.
State the proper forms of hypotheses for one-sample hypothesis tests.
Correctly formulate hypotheses.
List the four possible outcome results from a hypothesis test.
Explain the difference between Type I and Type II errors.
State how to increase the power of a test.
Choose the proper test statistic for hypothesis tests involving means and proportions.
Explain how to draw a conclusion for one- and twotailed hypothesis tests.
Use p-values to draw conclusions about hypothesis tests.
State the proper forms of hypotheses for two-sample hypothesis tests.
Select and use Excel Analysis Toolpak procedures for two-sample hypothesis tests.
Explain the purpose of analysis of variance.
Use the Excel ANOVA tool to conduct an analysis of variance test.
List the assumptions of ANOVA.
Conduct and interpret the results of a chi-square test for independence.
A company is considering two different campaigns, A and B, for the promotion of their product. Two tests are conducted in two market areas with identical consumer characteristics, and in a random sample of 60 customers who saw campaign A, 18 tried the product. In a random sample of 100 customers
A management institute checked the past records of applicants and the mean score calculated was 350. The administration is interested to know whether the quality of new applicants has changed or not. From the recent scores of 100 applicants, the mean is 365 with a standard deviation of 38. Does
Metropolitan Press hypothesizes that the average life of its largest Web press is 14,500 hours. They know that the standard deviation of press life is 2,100 hours. From a sample of 25 presses, the company find sample mean of 13,000 hours. At a 0.01 significance level, should the company conclude
Ice Cream Manufacture is to produce a new ice cream flavor. The company‘s marketing research department surveyed 6,000 families and 335 of them showed interest in purchasing the new flavor. A similar study made two year ago showed that 5% of the families would purchase the flavor. What should the
The manager of a store claims that 60% of the shoppers entering the store leave without making a purchase. Out of a sample of 50, it is found that 35 shoppers left without buying. Is the result consistent with the claim?
A sample of 400 athletes is found to have mean height of 171.38 cm. Can we call it a sample from a large population of mean height 171.17 and standard deviation of 3.30 cm?
A sample size of 22 with a mean of 8 and a standard deviation of 12.5 test the hypothesis that the value of the population mean is 70 against the assumption that it is more than 70. Use the 0.025 significant levels.
A car manufacturing firm is bringing out a new model. To figure out its advertising campaign, they want to determine whether the model appeal will be dependent on a particular age group. A sample of a customer survey revealed the following:Under 20 20–40 40–50 50 and over Total Liked 140 70 70
A survey of college students determined the preference for cell phone providers. The following data were obtained:Provider Gender T-Mobile AT&T Verizon Other Male 12 39 27 16 Female 8 22 24 12 Can we conclude that gender and cell phone provider are independent? If not, what implications does this
Are there significant differences in ratings of specific product/service attributes in the 2014 Customer Survey worksheet?
In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2014 significantly improved since 2010?
Have the data in the worksheet Defects After Delivery changed significantly over the past 5 years?
Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the proposed processes is better than the current process?
Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?
Explain the purpose of regression analysis and provide examples in business.
Use a scatter chart to identify the type of relationship between two variables.
List the common types of mathematical functions used in predictive modeling.
Use the Excel Trendline tool to fit models to data.
Explain how least-squares regression finds the bestfitting regression model.
Use Excel functions to find least-squares regression coefficients.
Use the Excel Regression tool for both single and multiple linear regressions.
Interpret the regression statistics of the Excel Regression tool.
Interpret significance of regression from the Excel Regression tool output.
Draw conclusions for tests of hypotheses about regression coefficients.
Interpret confidence intervals for regression coefficients
Calculate standard residuals.
List the assumptions of regression analysis and describe methods to verify them.
Explain the differences in the Excel Regression tool output for simple and multiple linear regression models.
Apply a systematic approach to build good regression models.
Explain the importance of understanding multicollinearity in regression models.
Build regression models for categorical data using dummy variables.
Test for interactions in regression models with categorical variables.
Identify when curvilinear regression models are more appropriate than linear models.
Each worksheet in the Excel file LineFit Data contains a set of data that describes a functional relationship between the dependent variable y and the independent variable x. Construct a line chart of each data set, and use the Excel Trendline tool to determine the best-fitting functions to model
A consumer products company has collected some data relating to the advertising expenditure and sales of one of its products:Advertising cost Sales$300 ╇ $7000$350 ╇ $9000$400 $10000$450 $10600 What type of model would best represent the data?Use the Excel Trendline tool to find the
Using the data in Excel file Loans, construct a scatter chart for monthly income versus loan amount and add a linear trendline. What is the regression model?If an individual has 7336 as monthly income, what would you predict the loan amount to be?
Using the results of fitting the Home Market Value regression line in Example 8.4, compute the errors associated with each observation using formula (8.3)and construct a histogram.
Set up an Excel worksheet to apply formulas (8.5)and (8.6) to compute the values of b0 and b1 for the data in the Excel file Home Market Value and verify that you obtain the same values as in Examples 8.4 and 8.5.
The managing director of a consulting group has the following monthly data on total overhead costs and professional labor hours to bill to clients:4 Overhead Costs Billable Hours$365,000 3,000$400,000 4,000$430,000 5,000$477,000 6,000$560,000 7,000$587,000 8,000a. Develop a trendline to identify
Using the data in Excel file Crime, apply the Excel regression tool using crime rate (CRIM) as the dependent variable and pupil-teacher ratio (PTRATIO)in the region as the independent variable.a. Interpret all key regression results, hypothesis tests, and confidence intervals in the output.b. Use
Using the data in the Excel file Credit Card Spending, develop a multiple linear regression model for estimating the average credit card expenditure as a function of both the income and family size. Predict the average expense of a family that has two members and an income of $188,000 per annum,
For the Car Sales data described in Problem 25, develop a regression model for selling price as a function of horsepower and manufacture year, incorporating an interaction term. What would be the predicted price for a car manufactured in either 2002 or 2003 with a horsepower of 69? How do these
Cost functions are often nonlinear with volume because production facilities are often able to produce larger quantities at lower rates than smaller quantities.5 Using the following data, apply simple linear regression, and examine the residual plot. What do you conclude? Construct a scatter chart
A product manufacturer wishes to determine the relationship between the shelf space of the product and its sales. Past data indicates the following sales and shelf space in its stores.Sales Shelf Space$25,000 5 square feet$15,000 3.2 square feet$28,000 5.4 square feet$30,000 6.1 square feet$17,000
Use XLMiner and best subsets with stepwise selection to find the best model points per game for the National Football League data (see Problem 23).
In reviewing the PLE data, Elizabeth Burke noticed that defects received from suppliers have decreased (worksheet Defects After Delivery). Upon investigation, she learned that in 2010, PLE experienced some quality problems due to an increasing number of defects in materials received from suppliers.
Define business analytics. Appendix
Explain why analytics is important in today’s business environment. Appendix
State some typical examples of business applications in which analytics would be beneficial. Appendix
Summarize the evolution of business analytics and explain the concepts of business intelligence, operations research and management science, and decision support systems. Appendix
Explain and provide examples of descriptive, predictive, and prescriptive analytics. Appendix
State examples of how data are used in business. Appendix
Explain the difference between a data set and a database. Appendix
Define a metric and explain the concepts of measurement and measures. Appendix
Explain the difference between a discrete metric and continuous metric, and provide examples of each. Appendix
Describe the four groups of data classification, categorical, ordinal, interval, and ratio, and provide examples of each. Appendix
Explain the concept of a model and various ways a model can be characterized. Appendix
Define and list the elements of a decision model. Appendix
Define and provide an example of an influence diagram. Appendix
Use influence diagrams to build simple mathematical models. Appendix
Use predictive models to compute model outputs. Appendix
Explain the difference between uncertainty and risk. Appendix
Define the terms optimization, objective function, and optimal solution. Appendix
Explain the difference between a deterministic and stochastic decision model. Appendix
List and explain the steps in the problem-solving process. Appendix
1. Will analytics solve the problem? Will the tool enable a better solution? Should other non analytical solutions be used? Are there organizational or other issues that must be resolved? Often, what may appear to be an analytical problem may actually be rooted in problems of incentive
2. Can we leverage an existing solution? Before“reinventing the wheel,” can existing solutions address the problem? What are the costs and benefits?
3. Is a decision model really needed? Can simple decision guidelines be used instead of a formal decision tool?
1. What is your gender?Male Female
2. What is your age?
3. What is the highest level of education you have completed?Some High School Classes High School Diploma Some Undergraduate Courses Associate Degree Bachelor Degree Master Degree J.D.M.D.Doctorate Degree
4. What is your annual income?$0 to 6$10,000$10,000 to 6$20,000$20,000 to 6$30,000$30,000 to 6$40,000$40,000 to 6$50,000$50,000 to 6$60,000$60,000 to 6$70,000$70,000 to 6$80,000$80,000 to 6$90,000$90,000 to 6$110,000$110,000 to 6$130,000$130,000 to 6$150,000$150,000 or More
5. On average, how much do you pay for beauty and hygiene products or services per year? Include references to the following products: soap, deodorant, shampoo, conditioner, lotion, perfume, cologne, makeup, chemical hair color, razors, skin care, feminine care, and salon services.
6. On average, how many beauty and hygiene advertisements, if at all, do you think you view or hear per day? Include references to the following advertisements:television, billboard, Internet, radio, newspaper, magazine, and direct mail.
7. On average, how many of those advertisements, if at all, specifically subscribe to gender roles and stereotypes?
8. On the following scale, what role, if any, do these advertisements have in reinforcing specific gender stereotypes?Drastic Influential Limited Trivial None
9. To what extent do you agree that empowerment advertising, which explicitly communicates the unique differences in each individual, would help transform cultural gender stereotypes?Strongly agree Agree Somewhat agree Neutral Somewhat disagree Disagree Strongly disagree
10. On average, what percentage of advertisements that you view or hear per day currently utilize empowerment advertising?
1. Discuss how business analytics can be used in sports, such as tennis, cricket, football, and so on. Identify as many opportunities as you can for each.
2. A multinational hotel chain has been implementing analytics digital marketing to its customers. However, the responses to the digital campaigns have not been favorable, and the revenue generation has not been as expected. Currently, they are trying to solve this problem by focusing on similar
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