market. We then characterize empirically the factors which drive price changes, noting clear evidence of firm heterogeneity in the choice of pricing strategy. Finally, we develop a framework for simulating counterfactual market settings, using the simulations to examine counterfactuals involving different mixes of firms according to pricing strategies. JEL Codes: L11, C73, D21, L81 Contact Information: Ellison: Department of Economics, M.I.T., 50 Memorial Drive, Cambridge, MA 02142; tel. (617)
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QNT-351 Discussion Question Responses * DQ#1: What is the importance of statistics in business decision making? Describe a business situation where statistics was used in making a decision. 1. Using statistics to evaluate the performance of your business. Taking all factors into account, determine whether you are making or losing money. In addition, determine the trend of your business. For example, determine whether, over time, you are making more or less profit (or loss). Track the share
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Analysis of Simulation JCT2-Supply Chain Robert Hilton January 2014 Simulation Results Cumulative industry results for last four quarters ending in quarter: 4 | | Minimum | Maximum | Average | Realtech | Total Overall | 0.00 | 916.17 | 25.93 | 0.00 | Financial Performance | -72.01 | 266.30 | 24.14 | -5.20 | Market Performance | 0.00 | 0.68 | 0.27 | 0.17 | Marketing Effectiveness | 0.00 | 0.82 | 0.58 | 0.60 | Investment in Future | 0.00 | 298,149.15 | 299.69 | 1.77
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Jim Albert and Ruud H. Koning (eds.) Statistical Thinking in Sports CRC PRESS Boca Raton Ann Arbor London Tokyo Contents 1 Introduction Jim Albert and Ruud H. Koning 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Patterns of world records in sports (2 articles) . . . . . . . 1.1.2 Competition, rankings and betting in soccer (3 articles) . . 1.1.3 An investigation into some popular baseball myths (3 articles) . . . . . . . . . . . . . . . .
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TOPic: DECISION SUPPORT SYSTEMS: AN OVERVIEW AND ITS ROLE IN BUSINESS Introduction A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance. Typical information that a decision support application might gather and present are: * Inventories
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Perishable Inventory Theory: A Review Author(s): Steven Nahmias Source: Operations Research, Vol. 30, No. 4 (Jul. - Aug., 1982), pp. 680-708 Published by: INFORMS Stable URL: http://www.jstor.org/stable/170438 . Accessed: 04/05/2011 21:21 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission
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Journal of Data Science 2(2004), 231-244 Estimating Vehicle Speed from Traffic Count and Occupancy Data Martin L. Hazelton University of Western Australia Abstract: Automatic vehicle detectors are now common on road systems across the world. Many of these detectors are based on single inductive loops, from which data on traffic volumes (i.e. vehicle counts) and occupancy (i.e. proportion of time during which the loop is occupied) are available for 20 or 30 second observational periods. However
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receive a sentence of seventeen months for the same crime. With this belief in mind, statistician Kristian Lum and her colleagues conducted a study to find out why imprisonment is more transmissible among blacks than whites. They created a computer simulation to see how an incarceration epidemic could develop. They created a virtual community of 8000 people, assigning each person a gender, a partner, some number of children, siblings, friends, and a lifespan. About 60,000 relationships were developed
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cash asset acquisition, asset acquisition recording procedures for procurement and reporting asset procedures. This procedure is combined as a procedure that is both sequences. But in fact this procedure is fractured and there is a delay when the simulation is large enough at the end of each procedure. Then the inventory procedure carries the merger between inventory and inventory compilation university faculty. This is also done because it has a sequential flow and delay occur at the end of the inventory
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University of Florence Faculty of Economy Master’s Degree in Bank, Insurance and Financial Markets Thesis in Applied Statistics for Banks and Insurances Credit Risk Models: Single Firm Default and Contagion Default Analysis Supervisor: P rof essor Fabrizio Cipollini Student: Marco Gambacciani Academic Year 2009/2010 Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Structural Models 1.1 Terminal Default . . . . . . . . . . . . 1.2 First Passage Models
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