Case Analyses Project

Transcription

1 Case Analyses Project Deliverables for each Case Analysis Project 1. A computer composed and printed paper copy of the case analysis report must be delivered on the due date. Relevant statistical reports and graphs must be properly integrated in the body of the written report or appended at the end of the report as appropriate. You will need to use both Word and Excel to prepare this report. Guidelines for the content and format of this report are described below. 1.1 The report must contain both the questions and answers to the questions in a case. 1.2 The language of the report must be plain and not filled with too many statistical jargons. 1.3 Tables, charts and or equations must be nicely placed for readability of the report. 1.4 The cover page must contain the full names of each member of the presenting team. 1.5 The title of the case must match perfectly with the title of the case report. 1.6 There must be at least three multiple choice questions in the report. There should be five answer choices for each question labeled a through e and the correct answer must not be revealed to the class until all students have had a chance to try to answer each question. 2. Submit the (1) MS Word and (2) Excel files electronically in the folder specified in the computer in your classroom. Name both the Word and the Excel file with the name of the case. Place these files in the specified folder right before presenting your case in front of the class. 3. A PowerPoint slide show must be used to guide the presentation of the research report in front of the class. Submit the Power Point file electronically in the folder specified in the computer in your classroom. Name the file with the name of the case. 4. Each team will perform two roles: (1) presenter and (2) interlocutor. Each team's performances will be evaluated twice--once in the role of presenter and once in the role of interlocutor. Your instructor and your classmates will be your evaluators. Each evaluator will give an evaluation report and feedback so that performers can learn how their performances were perceived and evaluated by the instructor and by classmates. Guidelines for the Oral Presentation of Cases Each case has been assigned to two competing teams A and B. When team A, playing the role of presenter, presents its report on a case, team B, in its role as interlocutor, will ask questions and engage members of team A in a critical, substantial conversation or debate related to the case. The roles will be switched for each case so that both teams associated with each case will alternate in playing both roles--presenter and interlocutor. An interlocutor is someone who takes part in talks as a representative of another person or organization. When a team plays the role of interlocutor, it will take part in talks, discussions, conversations or debates on behalf of those who may ask for proofs and explanations, or identify and challenge the assumptions underlying what the presenting team is presenting. Only the force of logic can be used politely during exchanges that take place between the presenting team and the interlocutors so that the end result for every student will be a deeper and clearer understanding of the concepts underlying each case. The presenting team will write and ask at least three multiple choice questions that summarize the key lessons of statistics learned in the context of their specific case. Each of these multiple choice questions must have only one answer that is clearly the best compared to the other four alternatives. These questions must be in the written report, and in the Power Point slide show used during the presentation of a case analysis report. The presenting team may ask the interlocutors to try to answer these questions first. If their answers are not satisfactory, any student from the class may try to answer these questions. However, the presenting team must eventually point out which of the alternatives is the best answer to the question and why. After necessary editing, some of the case-based questions written by students may be used by the instructor for Test 4 which will cover chapters 8, 9 and 12. Please look up your name, your case name, and due date from the chart below. Friday, October 22, 2010 Page 1 of 9

2 Section A TR 12:30p.m. to 1:45p.m. Name Case# CaseTitle DueDate Group Anguiano, Greg S. 8-2 Gulf Real Estate Properties 2-Nov-10 A Jones, Elizabeth 8-2 Gulf Real Estate Properties 2-Nov-10 A Willis, Heather D. 8-2 Gulf Real Estate Properties 2-Nov-10 A Cano, Mia J. 8-2 Gulf Real Estate Properties 2-Nov-10 B Weeden, Zachary D. 8-2 Gulf Real Estate Properties 2-Nov-10 B Allen, Michele L. 8-2 Gulf Real Estate Properties 2-Nov-10 B Robinson, Nathan D. 8-3 Metropolitan Research, Inc. 2-Nov-10 A Gisriel, Derek R. 8-3 Metropolitan Research, Inc. 2-Nov-10 A Ahmed, Saquib 8-3 Metropolitan Research, Inc. 2-Nov-10 A Montoisy, Laurent 8-3 Metropolitan Research, Inc. 2-Nov-10 B Cholick, Kelly A. 8-3 Metropolitan Research, Inc. 2-Nov-10 B McMullen, Emily B. 8-3 Metropolitan Research, Inc. 2-Nov-10 B Holsonback, Kayla R. 9-2 Unemployment Study 9-Nov-10 A Telles, Elizabeth K. 9-2 Unemployment Study 9-Nov-10 A Pang, Jia 9-2 Unemployment Study 9-Nov-10 A Thomas, Samantha D. 9-2 Unemployment Study 9-Nov-10 B Hutchins, Jordan L. 9-2 Unemployment Study 9-Nov-10 B Moralez, Eric I. 9-2 Unemployment Study 9-Nov-10 B Hoang, Nhung T. 9-1 Quality Associates, Inc. 9-Nov-10 A Shanley, Jordan D. 9-1 Quality Associates, Inc. 9-Nov-10 A Riedesel, Hailey J. 9-1 Quality Associates, Inc. 9-Nov-10 A Cadario Lopez, Sebastian 9-1 Quality Associates, Inc. 9-Nov-10 B Cepeda, Edgar R. 9-1 Quality Associates, Inc. 9-Nov-10 B Mendez, Jose D. 9-1 Quality Associates, Inc. 9-Nov-10 B Arnold, Steven T Major League Baseball Team Values 18-Nov-10 A Wrinkle, Scott D Major League Baseball Team Values 18-Nov-10 A Stewart, Zach I Major League Baseball Team Values 18-Nov-10 A Bower, Meredith E Major League Baseball Team Values 18-Nov-10 B Keithley, Kyndera K Major League Baseball Team Values 18-Nov-10 B Salas, Eloisa 12-4 Major League Baseball Team Values 18-Nov-10 B Guarderas Williams, Alvaro J Spending and Student Achievement 18-Nov-10 A Kim, Sang M Spending and Student Achievement 18-Nov-10 A Norris, Andrew R Spending and Student Achievement 18-Nov-10 A Friesenhahn, Chelsea A Spending and Student Achievement 18-Nov-10 B McCall, Amanda S Spending and Student Achievement 18-Nov-10 B Enriquez, Elizabeth M Spending and Student Achievement 18-Nov-10 B Lopez Corredor, Juan C U.S. Department of Transportation 18-Nov-10 A Murphy, Danielle R U.S. Department of Transportation 18-Nov-10 A Romero, Anthony E U.S. Department of Transportation 18-Nov-10 A Gamez, Marissa A U.S. Department of Transportation 18-Nov-10 B Langford, James 12-2 U.S. Department of Transportation 18-Nov-10 B Manzo Jr, Francisco A Friday, October U.S. 22, 2010 Department of Transportation Page 2 of 9 18-Nov-10 B

3 Section B TR 5:30p.m. to 6:45p.m. Name Case# CaseTitle DueDate Group Kayhan, Mehmed M. 8-2 Gulf Real Estate Properties 2-Nov-10 A Halmagyi, Ileana J. 8-2 Gulf Real Estate Properties 2-Nov-10 A Rodriguez, Valerie 8-2 Gulf Real Estate Properties 2-Nov-10 A Hucker, Bettsy D. 8-2 Gulf Real Estate Properties 2-Nov-10 B Fancher, Brian R. 8-2 Gulf Real Estate Properties 2-Nov-10 B Alaniz, Zina U. 8-2 Gulf Real Estate Properties 2-Nov-10 B Garcia, Cynthia I. 9-1 Quality Associates, Inc. 9-Nov-10 A Schoonover, Caleb L. 9-1 Quality Associates, Inc. 9-Nov-10 A Espitia, Michael A. 9-1 Quality Associates, Inc. 9-Nov-10 A Randolph, Jason T. 9-1 Quality Associates, Inc. 9-Nov-10 B Snider, Mackenzie E. 9-1 Quality Associates, Inc. 9-Nov-10 B Ramirez, Daniel 9-1 Quality Associates, Inc. 9-Nov-10 B Anderson, Angelia K Spending and Student Achievement 18-Nov-10 A Cisneros, Joe M Spending and Student Achievement 18-Nov-10 A Bernwanger, Britt L Spending and Student Achievement 18-Nov-10 A Yanez, Joshua R Spending and Student Achievement 18-Nov-10 A Gao, Yang 12-1 Spending and Student Achievement 18-Nov-10 B Garcia, Kandice M Spending and Student Achievement 18-Nov-10 B Hair, Dennis R Spending and Student Achievement 18-Nov-10 B Gonzalez, Anabel 12-1 Spending and Student Achievement 18-Nov-10 B Data for the cases can be found in the CD that you got with your textbook. If any student needs to collect the data set from the instructor because you lost your CD, please contact the instructor individually. The actual cases are in the following pages. Friday, October 22, 2010 Page 3 of 9

4 Case Problem 8-2: Gulf Real Estate Properties Due on Nov 2, 2010 Gulf Real Estate Properties, Inc., is a real estate firm located in southwest Florida. The company, which advertises itself as expert in the real estate market, monitors condominium sales by collecting data on location, list price, sale price, and number of days it takes to sell each unit. Each condominium is classified as Gulf View if it is located directly on the Gulf of Mexico or No Gulf View if it is located on the bay or a golf course, near but not on the Gulf. Sample data from the Multiple Listing Service in Naples, Florida, provided recent sales data for 40 Gulf View condominiums and 18 No Gulf View condominiums. Prices are in the thousands of dollars. The data are shown in Table Use appropriate descriptive statistics to summarize each of the three variables for the 40 Gulf View condominiums. 2. Use appropriate descriptive statistics to summarize each of the three variables for the 18 No Gulf View condominiums. 3. Compare your summary results. Discuss any specific statistical results that would help a real estate agent understand the condominium market. 4. Develop a 95% confidence interval estimate of the population mean sales price and population mean number of days to sell for Gulf View condominiums. Interpret your results. 5. Develop a 95% confidence interval estimate of the population mean sales price and population mean number of days to sell for No Gulf View condominiums. Interpret your results. 6. Assume the branch manager requested estimates of the mean selling price of Gulf View condominiums with a margin of error of $40,000 and a mean selling price of No Gulf View condominiums with a margin of error of $15,000. Using 95% confidence, how large should the sample sizes be? 7. Gulf Real Estate Properties just signed contracts for two new listings: Gulf View condominium with a list price of $589,000 and a No Gulf View condominium with a list price of $285,000. What is your estimate of the final selling price and number of days required to sell each of these units? Friday, October 22, 2010 Page 4 of 9

5 Case Problem 8-3: Metropolitan Research, Inc. Due on Nov 2, 2010 Metropolitan Research, Inc., a computer research organization, conducts surveys designed to evaluate a wide variety of products and services available to consumers. In one particular study, Metropolitan looked at consumer satisfaction with the performance of automobiles produced by a major Detroit manufacturer. A questionnaire sent to owners of one of the manufacturer s full-sized cars revealed several complaints about early transmission problems. To learn more about the transmission failures, Metropolitan used a sample of actual transmission repairs provided by a transmission repair firm in the Detroit area. The following data show the actual number of miles driven for 50 vehicles at the time of transmission failure. 1. Use appropriate descriptive statistics to summarize the transmission failure data. 2. Develop a 95% confidence interval for the mean number of miles driven until transmission failure for the population of automobiles with transmission failure. Provide a managerial interpretation of the interval estimate. 3. Discuss the implication of your statistical finding in terms of the belief that some owners of the automobiles experienced earlier transmission failures. 4. How many repair records should be sampled if the research firm wants the population mean number of miles driven until transmission failure to be estimated with a margin of error of 5,000 miles? Use 95% confidence. 5. What other information would you like to gather to evaluate the transmission failure problems more fully? Friday, October 22, 2010 Page 5 of 9

6 Chapter 9 Case Problem 9-1: Quality Associates, Inc. Due on Nov 9, 2010 Quality Associates, Inc., a consulting firm, advises its clients about sampling and statistical procedures that can be used to control the manufacturing processes. In one particular application, a client gave Quality Associates a sample of 800 observations taken during a time in which that client s process was operating satisfactorily. The sample standard deviation for these data was 0.21; hence, with so much data, the population standard deviation was assumed to be Quality associates then suggested that random samples of size 30 be taken periodically to monitor the process on an ongoing basis. By analyzing the new samples, the client could quickly learn whether the process was operating satisfactorily. When the process was not operating satisfactorily, corrective action could be taken to eliminate the problem. The design specification indicated the mean for the process should be 12. The hypothesis test suggested by Quality Associates follows. H₀: μ = 12 H a : μ 12 Corrective action will be taken any time H₀ is rejected. The following samples were collected at hourly intervals during the first day of operation of the new statistical process control procedure. These data are available in the data set Quality. 1. Conduct a hypothesis test for each sample at the 0.01 level of significance and determine what action, if any, should be taken. Provide the test statistic and p-value for each test. 2. Compute the standard deviation for each of the four samples. Does the assumption of 0.21 for the population standard deviation appear reasonable? 3. Compute limits for the sample mean x-bar around μ = 12 such that as long as a new sample mean is within those limits, the process will be considered to be operating satisfactorily. If x-bar exceeds the upper limit or if x-bar is below the lower limit, corrective action will be taken. These limits are referred to as upper and lower control limits for quality control purposes. 4. Discuss the implications of changing the level of significance to a larger value. What mistake or error could increase if the level of significance is increased? Friday, October 22, 2010 Page 6 of 9

7 Case Problem 9-2: Unemployment Study Due on Nov 9, 2010 Each month the U.S. Bureau of Labor Statistics publishes a variety of unemployment statistics, including the number of individuals who are unemployed and the mean length of time the individuals have been unemployed. For November 1998, the Bureau of Labor Statistics reported that the national mean length of time of unemployment was 14.6 weeks. The mayor of Philadelphia requested a study on the status of unemployment in the Philadelphia area. A sample of 50 unemployed residents of Philadelphia included data on their age and the number of weeks without a job. A portion of the data collected in November 1998 follows. The complete data set is available in the data file BLS. 1. Use descriptive statistics to summarize the data. 2. Develop a 95% confidence interval estimate of the mean age of unemployed individuals in Philadelphia. 3. Conduct a hypothesis test to determine whether the mean duration of unemployment in Philadelphia is greater than the national mean duration of 14.6 weeks. Use a 0.01 level of significance. What is your conclusion? 4. Is there a relationship between the age of an unemployed individual and the number of weeks of unemployment? Explain. Friday, October 22, 2010 Page 7 of 9

8 Chapter 12 Case Problem 12-1: Spending and Student Achievement Due on Nov 18, 2010 Is the educational achievement level of students related to how much the state in which they reside spends on education? In many communities taxpayers are asking this important question as school districts request tax revenue increases for education. In this case, you will be asked to analyze data on spending and achievement scores in order to determine whether there is any relationship between spending and student achievement in the public schools. The federal government s National Assessment of Educational Progress (NAEP) program is frequently used to measure the educational achievement of students. Table 12.8 shows the total current spending per pupil per year and the composite NAEP test score for 35 states that participate in the NAEP program. These data are available on the CD accompanying the text in the file named NAEP. The composite test score is the sum of the math, science, and reading scores on the 1996 (1994 for reading) NAEP test. Pupils tested are in grade 8, except for reading, which is given to fourth-graders only. The maximum possible score is 1,300. Table 12.9 shows the spending per pupil for 13 states that did not participate in relevant NAEP surveys. These data were reported in an article on spending and achievement level appearing in Forbes (November 3, 1997). 1. Develop numerical and graphical summaries of the data. 2. Use regression analysis to investigate the relationship between the amount spent per pupil and the composite score on the NAEP test. Discuss your findings. 3. Do you think that the estimated regression equation developed for these data could be used to estimate the composite test scores for the states that did not participate in the NAEP program? 4. Suppose that you only considered states that spend at least $4,000 per pupil but not more than $6,000 per pupil. For these states, does the relationship between the two variables appear to be any different than for the complete data set? Discuss the results of our findings and whether you think deleting states with spending les than $4,000 per ear and more than $6,000 per pupil is appropriate. 5. Develop estimates of the composite test scores for the states that did not participate in the NAEP program. 6. Based upon your analyses, do you think that the educational achievement level of students is related to how much the state spends on education? Friday, October 22, 2010 Page 8 of 9

9 Case Problem 12-2: U.S. Department of Transportation Due on Nov 18, 2010 As part of a study on transportation safety, the U.S. Department of Transportation collected data on the number of fatal accidents per 1,000 licenses and the percentage of licensed drivers under the age of 21 in a sample of 42 cities. Data collected over a one-year period follow. These data are available on the CD accompanying the text in the file named Safety. 1. Develop numerical and graphical summaries of the data. 2. Use regression analysis to investigate the relationship between the numbers of fatal accidents and the percentage of drivers under the age of 21. Discuss your findings. 3. What conclusion and recommendations can you derive from your analysis? =============================================================== Case Problem 12-4: Major League Baseball Team Values Due on Nov 18, 2010 A group led by John Henry paid $700 million to purchase the Boston Red Sox, even though the Red Sox have no won the World Series since 1918 and posted an operating loss of $11.4 million for Moreover, Forbes magazine estimates that the current value of the team is actually $426 million. Forbes attributes the difference between the current value for a team and the price investors are willing to pay to the fact that purchase of a team often includes the acquisition of a grossly undervalued cable network. For instance, in purchasing the Boston Red Sox, the new owners also got an 80% interest in the New England Sports Network. Table shows data for the 30 major league teams (Forbes, April 15, 2002). The column labeled Value contains the values of the teams based on current stadium deals, without deduction for debt. The column labeled Income indicates the earnings before interest, taxes, and depreciation. 1. Develop numerical and graphical summaries of the data. 2. Use regression analysis to investigate the relationship between value and income. Discuss your findings. 3. Use regression analysis to investigate the relationship between value and revenue. Discuss your findings. 4. What conclusion and recommendations can you derive from your analysis? Friday, October 22, 2010 Page 9 of 9