14-10-12 下午1:09 ECON-3740 Introduction to Econometrics - Fall‚ 2014 Instructor: D Prescott Due date: Thursday‚ 16 October‚ 3pm Submit Reports to D Prescott’s Office‚ Room 733 MacKinnon Report #1 - Instructions. No reports will be accepted after the deadline. Please submit what you have completed by the deadline. See the course web page for additional information on programming and spreadsheet hints. BE SURE TO USE THE DATA SET ASSIGNED TO YOU Grades will be assigned to each section. The
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(cents) • X4 = Real retail price of beef per lb. (cents) • X5 = Composite real price of chicken substitutes per lb. Step 1) Check for the overall utility of the model The regression analysis output is given below. Regression Analysis: lbs. per Cap versus Real Disposa‚ Real Retail‚ ... The regression equation is lbs. per Capita Consumed = 39.5 + 0.00204 Real Disposable Income per Capi - 0.129 Real Retail Price of Chicken +
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References: [1] Cellular operators of India www.coai.com [2]Census 2001 censusindia.gov.in [3] Regression selection strategy & revealed priors; Edward Learner‚ J.of American stat Assoc‚ Vol-73 no-363(sept-1978)‚ pp-580-587. (jstor.org/stables/2286604) [4] The Logistic curve: A fitting technique; D.F.Phipps.‚ The Statician‚ Vol-24‚No-2‚(Jan-1975)‚pp-129-136. [5] The Acceptability of Regression solutions : Another look at computational accuracy.‚Albert E. Beaton‚ Donald R. Rubin & Jhon L.Barone
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BUAD 310 Spring 2013 Case Due by 4PM on Friday‚ May 3rd (in BRI 400C) In this case you will apply statistical techniques learned in the Regression part of BUAD 310. Please read the following instructions carefully before you start: • This assignment uses data from the file MagAds13S.XLS‚ which you can download from Blackboard. After you download the file go to Data → Load data → from file in StatCrunch to open it (you don’t need to change any of the options when loading this
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zero. Why? This just means that there is no linear correlation between all three variables advertising/location/price. 4) Run regressions for each sales variable (s1‚ s2‚ s3) using P‚ A‚ L and independent variables. What do the regressions imply about the effect on price? Of advertising? Of location? In sales period one the coefficients table of the regression reveals that there is statistical significance between the price variable and sales. It is a negative correlation which implies that
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Crusty Pizza Restaurant: Forecasting using Regressions Group One: Jenna Baseler and Zachary Kain MBA 610-T304 Introduction The purpose of this case is to determine which key variables drive Crusty Pizza Restaurant’s monthly profit and then forecast what the monthly profit would be for potential stores. Based off of this information we will be able to make a recommendation to Crusty Dough Pizza Restaurant on which stores they should open and which they avoid. The group was provided 60 restaurants’
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Chapter 12 Simple Linear Regression Case Problem 1: Measuring Stock Market Risk a. Selected descriptive statistics follow: Variable N Mean StDev Minimum Median Maximum Microsoft 36 0.00503 0.04537 -0.08201 0.00400 0.08883 Exxon Mobil 36 0.01664 0.05534 -0.11646 0.01279 0.23217 Caterpillar 36 0.03010 0.06860 -0.10060 0.04080 0.21850 Johnson & Johnson 36 0.00530 0.03487 -0.05917 -0.00148 0.10334
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A Case Study on Cost Estimation and Profitability Analysis at Continental Airlines Francisco J. Román Introduction In 2008‚ the senior management team at Continental Airlines‚ commanded by Lawrence Kellner‚ the Chairman and Chief Executive Officer‚ convened a special meeting to discuss the firm’s latest quarterly financial results. A bleak situation lay before them. Continental had incurred an operating loss of $71 million dollars—its second consecutive quarterly earnings decline that year
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October 14‚ 2012 Subject: Regression Model for 3G License Valuation Estimation ------------------------------------------------- Background As part of the European expansion plan‚ Eurotel is planning to bid on 3G licenses in Hungary‚ Russia and Turkey. Usually‚ the operator determines the maximum price to bid following three steps: 1. NPV analysis 2. Market Indicator Considerations 3. Game theory As a complement to this methodology‚ a multiple linear regression model will be proposed
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Chapter I Introduction Regression analysis is a statistical tool for the investigation of relationships between variables. The investigator seeks to ascertain the causal effect of one variable upon another—the effect of a price increase upon demand‚ for example‚ or the effect of changes in the money supply upon the inflation rate. To explore such issues‚ the investigator assembles data on the underlying variables of interest and employs regression to estimate the quantitative effect of the causal
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