ANALYSIS REPORT OF HOMES SOLD To develop a multiple linear regression model to help the firm identify the average resale value of homes in the Fayeetville area, we have collected information on a random sample of 50 homes sold in the Fayettville area over the first 8 months of 2011. This information was obtained from the Fayettville Multi-Listing Realty Service and thus, our sample only includes homes listed or sold by agents and companies that belong to the service. We put collected data into
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Property Crimes Case Study # 49 Applied Managerial Statistics: GM533 Virginia Davis, Lauren Holder, Stanley Philip and Andrea Watson Executive Summary The Property Crimes study examined data provided by various U.S. government agencies on crime rates in the fifty U.S. states. Other data studied were eight possible contributing factors such as per capita income, high school dropout rate, average precipitation, population density, and urbanization. Analysis revealed, of the eight possible
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Final Exam Study Guide (Revised 5/17/2011) In preparing for the Final Exam, it will serve you well to take a step back and reflect on the content, structure, and flow of the course. This will enable you to organize your notes, your completed homework and case problems, your annotated Minitab output, and your thoughts. The course is organized around the Terminal Course Objectives (TCOs) and each week builds on the preceding week’s concepts and skills. Each week introduces, explains, and demonstrates
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A linear regression is worth a maximum of 5 points; a multiple regression is worth a maximum of 10 points and both are worth 13 points. You must analyze the regression(s) that you do. The better job that you do, for instance, checking the residuals and for multicollinearity, the more points you get. If you choose to do a linear regression then you must compare the list price to the square footage. You are to project out the listing price of a home that has 2750 square feet. If you choose to do the
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Question 1 The primary objective of a for-profit firm is to ___________. Selected Answer: Correct Answer: 5 out of 5 points maximize shareholder value maximize shareholder value Question 2 5 out of 5 points The flat-screen plasma TVs are selling extremely well. The originators of this technology are earning higher profits. What theory of profit best reflects the performance of the plasma screen makers? Selected Answer: Correct Answer: innovation theory of profit innovation theory
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Annex A Basic Analysis | | Reciprocating | Scroll | All | Average Price | Europe | $ 31,31 | $ 38,60 | $ 32,28 | | Latin | $ 38,71 | Does not exist | $ 38,71 | | North | $ 32,43 | $ 34,69 | $ 33,11 | | Total | $ 33,73 | $ 35,67 | $ 34,08 | Average Volume | Europe | 111.307,69 | 88
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More Frequent Casino Shuttle Bus Service, More Guests Visiting Casino Objective of the Research – Casinos provide various free services in order to attract more guests, such as free shuttle bus service. But in fact, some passengers are just free riders and their destination may not be the casino. The objective of the research is to determine how strong the relationship between the frequencies of casino shuttle bus service and the numbers of guests visiting the casino. Hypothesis – More frequent
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MIT School of Business (MITSOB) Post Graduate Diploma in Management (PGDM) Backlog (April 2014) Semester II Term End Examination Subject: Operations Research (203) Total Marks: 50 Duration: 2½ Hrs. Instructions: 1) Formulate the problems in the answer sheet. 2) Students should write the steps and formulae used in the cells along with the final answer, in the answer sheet so that examiner will be able to evaluate the answers. 3) No marks will
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a = intercept of development Now by using excel, the summary output is- SUMMARY OUTPUT Regression Statistics Multiple R 0.990550883 R Square 0.981191053 Adjusted R Square 0.978056228 Standard Error 1.646537702 Observations 8 Y=a+bX Coefficients Standard Error t Stat Intercept of development -0.590295137 1.315862427 -0.448599432 Fund 0.021358358 0.001207251 17.69172457 The
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Closing, S&P 500, PHG, BA, Trend 2.) Regression Analysis: GE Closing versus S&P 500, PHG, BA, Trend Analysis of Variance Source DF Adj SS Adj MS F-Value P-Value Regression 4 3354.01 838.503 250.08 0.000 Error 67 224.65 3.353 Total 71 3578.66 Model Summary S R-sq R-sq(adj) R-sq(pred) 1.83110 93.72% 93.35% 92.32% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant -6.23 2.49
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