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business analytics data

Questions and Answers of Business Analytics Data

1. Valencia Products makes automobile radar detectors and assembles two models:LaserStop and SpeedBuster. The firm can sell all it produces. Both models use the same electronic components. Two of
• Use the Sensitivity Report to evaluate scenarios.
• Interpret the Solver Sensitivity Report.
• Use Solver for conducting what-if analysis of optimization models.
• List the four possible outcomes when solving a linear optimization model and recognize them from Solver messages.
• Explain how Solver works.
• Illustrate and solve two-variable linear optimization problems graphically.
• Interpret the Solver Answer Report.
• Use the standard and premium Solver add-ins to solve linear optimization models in Excel.
• Implement linear optimization models on spreadsheets.
• State the properties that characterize linear optimization models.
• Recognize different types of constraints in problem statements.
• Apply the four-step process to develop a mathematical model for an optimization problem.
16. The Excel file Myatt Steak House provides 5 years of data on key business results for a restaurant. Identify the leading and lagging measures, find the correlation matrix, and propose a
15. The Excel file Automobile Options provides data on options ordered together for a particular model of automobile. Develop a market basket analysis using the XLMiner association rules procedure
14. For the PC Purchase Data, identify association rules with the following input parameters for the XLMiner association rules procedure:a. support = 3; confidence = 90%b. support = 7; confidence =
13. The Excel file Credit Risk Data provides a database of information about loan applications, along with a classification of credit risk in column L. Convert the categorical data into numerical
12. The Excel file Credit Risk Data provides a database of information about loan applications along with a classification of credit risk in column L. Convert the categorical data into numerical
11. The Excel file Credit Risk Data provides a database of information about loan applications along with a classification of credit risk in column L. Convert the categorical data into numerical
10. Use logistic regression to classify the new data in the Excel file Modified Credit Decisions using only credit score and years of credit history as input variables.
9. Use discriminant analysis to classify the new data in the Excel file Modified Credit Decisions using only credit score and years of credit history as input variables.
8. Use the k-NN algorithm to classify the new data in the Excel file Modified Credit Approval Decisions using only credit score and years of credit history as input variables.
7. Cluster the records in the Excel file Ten Year Survey. Create up to five clusters and analyze the results to draw conclusions about the survey.
6. Apply cluster analysis to the Excel file Sales Data, using the input variables Percent Gross Profit, Industry Code, and Competitive Rating. Create four clusters and draw conclusions about the
5. Apply cluster analysis to the numerical data in the Excel file Credit Approval Decisions.Analyze the clusters and determine if cluster analysis would be a useful classification method for
4. For the Colleges and Universities data, use XLMiner to find four clusters using each of the other clustering methods (see Figure 12.5); compare the results with Example 12.1.
3. For the four clusters identified in Example 12.1, find the average and standard deviations of each numerical variable for the schools in each cluster and compare them with the averages and
2. For the Excel file Colleges and Universities, normalize each column of the numerical data (that is; compute a z-score for each of the values) and then compute the Euclidean distances between the
1. Compute the Euclidean distance between the following sets of points:a. (2,5) and (8,4)b. (2, -1, 3) and (8, 15, -5)
• Use XLMiner to develop association rules.
• Describe association rule mining and its use in market basket analysis.
• Explain the purpose of classification methods, how to measure classification performance, and the use of training and validation data.
• Apply cluster analysis techniques using XLMiner.
22. J&G Bank receives a large number of credit-card applications each month, an average of 30,000 with a standard deviation of 4,000, normally distributed. Approximately 60% of them are approved, but
21. Refer back to the college admission director scenario (Problem 25 in Chapter 8).Develop a spreadsheet model and identify uncertain distributions that you believe would be appropriate in order to
20. The retirement planning model described in Chapter 8 (Figure 8.6) assumes that the data in rows 5–8 of the spreadsheet are the same for each year of the model.Comment on the realism of this
19. Review the retirement-planning situation described in Chapter 8 (Figure 8.6).Modify the spreadsheet to include the assumptions that the annual salary increase is triangular with a minimum of 1%,
18. For the Hyde Park Surgery Center scenario described in Problem 22 in Chapter 8, suppose that the following assumptions are made. The number of patients served the first year is uniform between
17. Develop and analyze a simulation model for Koehler Vision Associates (KVA)in Problem 10 of Chapter 8 with the following assumptions. The weekly demand averages 175, but anywhere between 10% and
16. Develop a simulation model for a 3-year financial analysis of total profit based on the following data and information. Sales volume in the first year is estimated to be 100,000 units and is
15. A plant manager is considering investing in a new $30,000 machine. Use of the new machine is expected to generate a cash flow of about $8,000 per year for each of the next 5 years. However, the
14. Develop a Monte Carlo simulation model for the garage-band in Problem 4 in Chapter 8 with the following assumptions. The expected crowd is normally distributed with mean of 3,000 and standard
13. The manager of the extended-stay hotel in Problem 16 of Chapter 8 believes that the number of rooms rented during any given month has a triangular distribution with minimum 32, most likely 38,
12. Using the profit model developed in Chapter 8, implement a financial simulation model for a new product proposal and determine a distribution of profits using the discrete distributions below for
11. Simulate the newsvendor model for the pharmacy situation described in Problem 9 of Chapter 8. Use the IntUniform distribution in Risk Solver Platform to model the demand and find the distribution
10. Use the Newsvendor Model spreadsheet to set up and run a Monte Carlo simulation assuming that demand is Poisson with a mean of 45 but a minimum value of 40 (use the lower cutoff parameter in the
9. For the Moore Pharmaceuticals model, suppose that analysts have made the following assumptions:• R&D costs: Triangular($500, $700, $800) in millions of dollars• Clinical trials costs:
8. For the profit model developed in Example 8.2 in Chapter 8 and in Figure 8.2, suppose that the demand is triangular with a minimum of 35,000, maximum of 60,000 and most likely value of 50,000;
7. Suppose that several variables in the model for the economic value of a customer in Example 8.1 in Chapter 8 are uncertain. Specifically, assume that the revenue per purchase is normal with a mean
6. For the Outsourcing Decision Model, suppose that the demand volume is lognormally distributed with a mean of 1,500 and standard deviation of 500. What is the distribution of the cost differences
5. Use Risk Solver Platform to simulate the Outsourcing Decision Model under the assumptions that the production volume will be triangular with a minimum of 800, maximum of 1,700, and most likely
4. Financial analysts often use the following model to characterize changes in stock prices:Pt = P0e(m-0.5s2)t+sZ2t where P0 = current stock price Pt = price at time t m = mean (logarithmic) change
3. For the new-product model in Problem 6 of Chapter 8, suppose that the first-year sales volume is normally distributed with a mean of 100,000 units and a standard deviation of 10,000. Use the
2. For the garage-band model in Problem 4 of Chapter 8, suppose that the expected crowd is normally distributed with a mean of 3,000 and standard deviation of 200.Use the NORM.INV function and a
1. For the market share model in Problem 1 of Chapter 8, suppose that the estimate of the percentage of new purchasers who will ultimately try the brand is uncertain and assumed to be normally
• Correlate uncertain variables in a simulation model using Risk Solver Platform.
• Compute confidence intervals for the mean value of an output in a simulation model.
• Use Risk Solver Platform to develop, implement, and analyze Monte Carlo simulation models.
• Use data tables to conduct simple Monte Carlo simulations.
• Explain the concept and importance of analyzing risk in business decisions.
21. Data in the Excel File Microprocessor Data shows the demand for one type of chip used in industrial equipment from a small manufacturer.a. Construct a chart of the data. What appears to happen
19. Choose an appropriate forecasting technique for the data in the Excel file Prime Rate and find the best forecasting model. Explain how you would use the model to forecast and how far into the
18. Choose an appropriate forecasting technique for the data in the Excel file Mortgage Rates and find the best forecasting model. Explain how you would use the model to forecast and how far into the
17. Choose an appropriate forecasting technique for the data in the Excel file Federal Funds Rates and find the best forecasting model. Explain how you would use the model to forecast and how far
16. Choose an appropriate forecasting technique for the data in the Excel file DJIA December Close and find the best forecasting model. Explain how you would use the model to forecast and how far
15. Choose an appropriate forecasting technique for the data in the Excel file Coal Consumption and find the best forecasting model. Explain how you would use the model to forecast and how far into
14. The Excel file Olympic Track and Field Data provides the gold medal–winning distances for the high jump, discus, and long jump for the modern Olympic Games. Develop forecasting models for each
13. Use the Holt-Winters no-trend model to find the best model to find forecasts for the next 12 months in the Excel file Housing Starts.
12. Use the Holt-Winters no-trend model to find the best model to forecast the next year of electricity usage in the Excel file Gas & Electric.
11. Develop a multiple regression model with categorical variables that incorporate seasonality for forecasting housing starts beginning in June 2006 using the data in the Excel file Housing Starts.
10. Develop a multiple regression model with categorical variables that incorporate seasonality for forecasting sales using the last three years of data in the Excel file New Car Sales.
9. Develop a multiple regression model with categorical variables that incorporate seasonality for forecasting the temperature in Washington, D.C., using the data for years 1999 and 2000 in the Excel
8. Consider the data in the Excel file Nuclear Power. Use simple linear regression to forecast the data. What would be the forecasts for the next 3 years?
7. Consider the data in the Excel file Consumer Price Index.a. Use simple linear regression to forecast the data. What would be the forecasts for the next 2 months?b. Use the double exponential
6. Consider the prices for the DJ Industrials in the Excel file Closing Stock Prices.The data appear to have a linear trend over the time period provided.a. Use simple linear regression to forecast
5. For the data in the Excel file Gasoline Prices do the following:a. Develop spreadsheet models for forecasting prices using simple moving average and simple exponential smoothing.b. Compare your
4. The Excel file Closing Stock Prices provides data for four stocks and the Dow Jones Industrials Index over a 1-month period.a. Develop spreadsheet models for forecasting each of the stock prices
3. The Excel file Energy Production & Consumption provides data on production, imports, exports, and consumption. Develop line charts for each “total” variable and identify key characteristics of
2. Search The Conference Board’s Web site to find economic forecasts and reports about their business cycle indicators. Write a short report about your findings.
1. Identify some business applications in which judgmental forecasting techniques such as historical analogy and the Delphi method would be useful.
• Apply XLMiner to different types of forecasting models.
• Identify the appropriate choice of forecasting model based on the characteristics of a time series.
23. The Helicopter Division of Aerospatiale is studying assembly costs at its Marseilles plant.6 Past data indicates the following labor hours per helicopter:Helicopter Number Labor Hours 1 2,000 2
22. 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
21. For the House Sales data described in Problem 21, develop a regression model for selling price as a function of lot cost and region.
20. A national homebuilder builds single-family homes and condominium-style townhouses. The Excel file House Sales provides information on the selling price, lot cost, type of home, and region of the
19. The State of Ohio Department of Education has a mandated ninth-grade proficiency test that covers writing, reading, mathematics, citizenship (social studies), and science. The Excel file Ohio
18. Use the p-value criterion to find a good model for predicting the number of points scored per game by football teams using the data in the Excel file National Football League.
17. The Excel file Golfing Statistics provides data for a portion of the 2010 professional season for the top 25 golfers.a. Find the best multiple regression model for predicting earnings/event as a
16. The Excel file Major League Baseball provides data on the 2010 season.a. Construct and examine the correlation matrix. Is multicollinearity a potential problem?b. Suggest an appropriate set of
15. Using the data in the Excel file Freshman College Data, identify the best regression model for predicting the first year retention rate. For the model you select, conduct further analysis to
14. The Excel file Credit Approval Decisions provides information on credit history for a sample of banking customers. Use regression analysis to identify the best model for predicting the credit
13. The Excel file Salary Data provides information on current salary, beginning salary, previous experience (in months) when hired, and total years of education for a sample of 100 employees in a
12. The Excel file Cereal Data provides a variety of nutritional information about 67 cereals and their shelf location in a supermarket. Use regression analysis to find the best model that explains
11. Using the data in the Excel file Home Market Value, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. Find a 95%
10. The Excel file Concert Sales provides data on sales dollars and the number of radio, TV, and newspaper ads promoting the concerts for a group of cities. Develop simple linear regression models
9. A deep-foundation engineering contractor has bid on a foundation system for a new building housing the world headquarters for a Fortune 500 company. A part of the project consists of installing
8. The Excel file National Football League provides various data on professional football for one season.a. Construct a scatter diagram for Points/Game and Yards/Game in the Excel file. Does there
7. Using the data in the Excel file Student Grades, apply the Excel Regression tool using the midterm grade as the independent variable and the final exam grade as the dependent variable.a. Interpret
6. Using the data in the Excel file Demographics, apply the Excel Regression tool using unemployment rate as the dependent variable and cost of living index as the independent variable.a. Interpret

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