...Basics of Statistics Jarkko Isotalo 30 20 10 Std. Dev = 486.32 Mean = 3553.8 N = 120.00 0 2400.0 2800.0 2600.0 3200.0 3000.0 3600.0 3400.0 4000.0 3800.0 4400.0 4200.0 4800.0 4600.0 5000.0 Birthweights of children during years 1965-69 Time to Accelerate from 0 to 60 mph (sec) 30 20 10 0 0 Horsepower 100 200 300 1 Preface These lecture notes have been used at Basics of Statistics course held in University of Tampere, Finland. These notes are heavily based on the following books. Agresti, A. & Finlay, B., Statistical Methods for the Social Sciences, 3th Edition. Prentice Hall, 1997. Anderson, T. W. & Sclove, S. L., Introductory Statistical Analysis. Houghton Mifflin Company, 1974. Clarke, G.M. & Cooke, D., A Basic course in Statistics. Arnold, 1998. Electronic Statistics Textbook, http://www.statsoftinc.com/textbook/stathome.html. Freund, J.E.,Modern elementary statistics. Prentice-Hall, 2001. Johnson, R.A. & Bhattacharyya, G.K., Statistics: Principles and Methods, 2nd Edition. Wiley, 1992. Leppälä, R., Ohjeita tilastollisen tutkimuksen toteuttamiseksi SPSS for Windows -ohjelmiston avulla, Tampereen yliopisto, Matematiikan, tilastotieteen ja filosofian laitos, B53, 2000. Moore, D., The Basic Practice of Statistics. Freeman, 1997. Moore, D. & McCabe G., Introduction to the Practice of Statistics, 3th Edition. Freeman, 1998. Newbold, P., Statistics for Business and Econometrics...
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...Forecasting MCQs Contains: in a random basis Gleim Book Gleim CD IMA - Retired 2005 IMA - Retired 2008 By: Mohamed “hengoo” to dvd4arab.com members Gleim CMA Test Prep: Part 1: Financial Planning, Performance, and Control (119 questions) [1] Gleim #: 1.5.133 -- Source: CMA 691 4-1 The expected monetary value of an act is the A. B. C. D. Revenue minus the costs for the act. Conditional profit (loss) for the best event times the probability of each event’s occurrence. Sum of the conditional profit (loss) for each event. Sum of the conditional profit (loss) for each event times the probability of each event’s occurrence. [Fact Pattern #1] Proper Propeller, Inc. plans to manufacture a newly designed high-technology propeller for airplanes. Proper Propeller forecasts that as workers gain experience, they will need less time to complete the job. Based on prior experience, Proper Propeller estimates a 70% cumulative learning curve and has projected the following costs. Cumulative number Manufacturing Projections of units produced Average cost per unit Total costs 1 2 $20,000 14,000 $20,000 28,000 [2] Gleim #: 1.3.98 -- Source: CMA 0408 1-148 (Refers to Fact Pattern #1) If Proper Propeller produces eight units, the average manufacturing cost per unit will be A. B. C. D. $14,000 $9,800 $1,647 $6,860 [3] Gleim #: 1.4.104 -- Source: CMA 1293 4-25 The four components of time series data are secular trend, cyclical...
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...listed (lowest price listed first), with better ranks contributing to firms' sales. Using a year's worth of hourly data, we document the pricing dynamics, cycles, and other patterns in this 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) 253-3821; fax. (617) 253-1330; email sellison@mit.edu. Snyder: Department of Economics, Dartmouth College, 301 Rockefeller Hall, Hanover, NH 03755; tel. (603) 646-0642, fax. (603) 646-2122, email chris.snyder@dartmouth.edu. Acknowledgments: The authors are grateful to Hongkai Zhang for superb research assistance and to Glenn Ellison for a number of useful conversations. 1. Introduction There is a vast and rich theoretical literature on the dynamics of repeated games. One conclusion of this literature is that many different market outcomes are possible. Full collusion, collusion on a focal price, cyclical markup patterns, and prices exactly tracking costs, are among the possibilities. This lack of a clear theoretical prediction suggests an important role for empirical...
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...level of chips and algorithms—both typical and ideal—which determine the endurance of a device. Our chip-level measurements show endurance far in excess of nominal values quoted by manufacturers, by a factor of as much as 100. We reverse engineer specifics of the Flash Translation Layers (FTLs) used by several devices, and find a close correlation between measured whole-device endurance and predictions from reverse-engineered FTL parameters and measured chip endurance values. We present methods based on analysis of operation latency which provide a non-intrusive mechanism for determining FTL parameters. Finally we present Monte Carlo simulation results giving numerical bounds on endurance achievable by any on-line algorithm in the face of arbitrary or malicious access patterns. 1 Introduction In recent years flash memory has entered widespread use, in embedded media players, photography, portable drives, and solid-state disks (SSDs) for traditional computing storage. Flash has become the first competitor to magnetic disk storage to gain significant commercial acceptance, with estimated shipments of 5 × 1019 bytes in 2009 [10], or more than the amount of disk storage shipped in 2005 [31]. Flash memory differs from disk in many characteristics; however, one which has particular importance for the design of storage systems is its...
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...recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. The consent of CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press LLC for such copying. Direct all inquiries to CRC Press LLC, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. Visit the CRC Press Web site at www.crcpress.com © 2002 by Chapman & Hall/CRC No claim to original U.S. Government works International Standard Book Number 1-5848-8245-X Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on...
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...importance and limitations of statistics. “A knowledge of statistics is like a knowledge of foreign language of algebra; it may prove of use at any time under any circumstance”……………………………………...Bowley. STRUCTURE: 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10 Introduction Meaning and Definitions of Statistics Types of Data and Data Sources Types of Statistics Scope of Statistics Importance of Statistics in Business Limitations of statistics Summary Self-Test Questions Suggested Readings 1.1 INTRODUCTION For a layman, ‘Statistics’ means numerical information expressed in quantitative terms. This information may relate to objects, subjects, activities, phenomena, or regions of space. As a matter of fact, data have no limits as to their reference, coverage, and scope. At the macro level, these are data on gross national product and shares of agriculture, manufacturing, and services in GDP (Gross Domestic Product). 1 At the micro level, individual firms, howsoever small or large, produce extensive statistics on their operations. The annual reports of companies contain variety of data on sales, production, expenditure, inventories, capital employed, and other activities. These data are often field data, collected by employing scientific survey techniques. Unless regularly updated, such data are the product of a one-time effort and have limited use beyond the situation that may have called for their collection. A student knows statistics more intimately as a subject of...
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...Data Analysis in SPSS Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 February 21, 2004 If you wish to cite the contents of this document, the APA reference for them would be DeCoster, J. (2004). Data Analysis in SPSS. Retrieved from http://www.stat-help.com/notes.html Heather Claypool Department of Psychology Miami University of Ohio 136 Benton Hall Oxford, OH 45056 All rights to this document are reserved Table of Contents Introduction ...................................................................................................................................................................1 Interactive Mode versus Syntax Mode ..........................................................................................................................2 Descriptive Statistics .....................................................................................................................................................4 Transformations.............................................................................................................................................................5 Compute ....................................................................................................................................................................5 Recode ............................................................................................................................
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...Our aim is to present the essential quantitative concepts and methods in a self-contained, nontechnical, and intuitive way. Our approach is structured in line with requirements for the CFA program. The material included is relevant to investment management by the ICFA, the Institute of Chartered Financial Analysts. We hope you find this appendix helpful. Use it to make your venture into investments more enjoyable. 1006 Appendix A 1007 A.1 PROBABILITY DISTRIBUTIONS Statisticians talk about “experiments,” or “trials,” and refer to possible outcomes as “events.” In a roll of a die, for example, the “elementary events” are the numbers 1 through 6. Turning up one side represents the most disaggregate mutually exclusive outcome. Other events are compound, that is, they consist of more than one elementary event, such as the result “odd number” or “less than 4.” In this case “odd” and “less than 4” are not mutually exclusive. Compound events can be mutually exclusive outcomes, however, such as “less than 4” and “equal to or greater than 4.”...
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...A SECOND COURSE IN STATISTICS REGRESSION ANALYISIS Seventh Edition William Mendenhall University of Florida Terry Sincich University of South Florida Prentice Hall Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London Toronto Madrid Delhi Milan Mexico Munich City Sao Paris Paulo Montreal Sydney Hong Kong Seoul Singapore Taipei Tokyo Editor in Chief: Deirdre Lynch Acquisitions Editor: Marianne Stepanian Associate Content Editor: Dana Jones Bettez Senior Managing Editor: Karen Wernholm Associate Managing Editor: Tamela Ambush Senior Production Project Manager: Peggy McMahon Senior Design Supervisor: Andrea Nix Cover Design: Christina Gleason Interior Design: Tamara Newnam Marketing Manager: Alex Gay Marketing Assistant: Kathleen DeChavez Associate Media Producer: Jean Choe Senior Author Support/Technology Specialist: Joe Vetere Manufacturing Manager: Evelyn Beaton Senior Manufacturing Buyer: Carol Melville Production Coordination, Technical Illustrations, and Composition: Laserwords Maine Cover Photo Credit: Abstract green flow, ©Oriontrail/Shutterstock Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and Pearson was aware of a trademark claim, the designations have been printed in initial caps or all caps. Library of Congress Cataloging-in-Publication Data Mendenhall, William. A second course in...
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...&r' 1 || i I Test Anxiety Applied Research, Assessment, and Treatment Interventions i I : fet 2nd Edition I « MARTY SAPP m: I H 1 ttTttTtttttrrtiTTITTtrrtttttttttTtrttiTTtrrttTtttTtTTTtttttiTttt TEST ANXIETY Applied Research, Assessment, and Treatment Interventions 2nd Edition Marty Sapp University Press of America, Inc. Lanham • New York • Oxford Copyright © 1999 by University Press of America,® Inc. 4720 Boston Way Lanham, Maryland 20706 12 Hid's Copse Rd. Cumnor Hill, Oxford 0X2 9JJ All rights reserved Printed in the United States of America British Library Cataloging in Publication Information Available Library of Congress Cataloging-in-Publication Data Sapp, Marty. Test Anxiety : applied research, assessment, and treatment interventions / Marty Sapp. —2nd ed. p. cm. Includes bibliographical references and indexes. 1. Test anxiety—Research—Statistical methods. 2. Social sciences—Statistical methods. I. Title. LB3060.6.S27 1999 371.26'01'9—dc21 99—22530 CIP ISBN 0-7618-1386-1 (cloth: alk. ppr.) fc/ The paper used in this publication meets the minimum requirements of American National Standard for Information Sciences—Permanence of Paper for Printed Library Materials, ANSI Z39.48—1984 To my students Preface to First Edition Preface to Second Edition This text is divided into three parts. Part I deals with applied research design and statistical methodology frequently occurring...
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...early in the design cycle is important because the cost to repair mistakes increases dramatically the later in the product life cycle that the error is detected. Another important application of simulation is in developing "virtual environments" , e.g., for training. Analogous to the holodeck in the popular science-fiction television program Star Trek, simulations generate dynamic environments with which users can interact "as if they were really there." Such simulations are used extensively today to train military personnel for battlefield situations, at a fraction of the cost of running exercises involving real tanks, aircraft, etc. Dynamic modeling in organizations is the collective ability to understand the implications of change over time. This skill lies at the heart of successful strategic decision process. The availability of effective visual modeling and simulation enables the analyst and the decision-maker to boost their dynamic decision by...
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...14. Data analysis and interpretation Concepts and techniques for managing, editing, analyzing and interpreting data from epidemiologic studies. Key concepts/expectations This chapter contains a great deal of material and goes beyond what you are expected to learn for this course (i.e., for examination questions). However, statistical issues pervade epidemiologic studies, and you may find some of the material that follows of use as you read the literature. So if you find that you are getting lost and begin to wonder what points you are expected to learn, please refer to the following list of concepts we expect you to know: Need to edit data before serious analysis and to catch errors as soon as possible. Options for data cleaning – range checks, consistency checks – and what these can (and can not) accomplish. What is meant by data coding and why is it carried out. Basic meaning of various terms used to characterize the mathematical attributes of different kinds of variables, i.e., nominal, dichotomous, categorical, ordinal, measurement, count, discrete, interval, ratio, continuous. Be able to recognize examples of different kinds of variables and advantages/disadvantages of treating them in different ways. What is meant by a “derived” variable and different types of derived variables. Objectives of statistical hypothesis tests (“significance” tests), the meaning of the outcomes from such tests, and how to interpret a p-value...
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...Appraising Research in Second Language Learning: A practical approach to critical analysis of quantitative research Graeme Keith Porte John Benjamins Publishing Company Appraising Research in Second Language Learning Language Learning and Language Teaching The LL< monograph series publishes monographs as well as edited volumes on applied and methodological issues in the field of language pedagogy. The focus of the series is on subjects such as classroom discourse and interaction; language diversity in educational settings; bilingual education; language testing and language assessment; teaching methods and teaching performance; learning trajectories in second language acquisition; and written language learning in educational settings. Series editors Birgit Harley Ontario Institute for Studies in Education, University of Toronto Jan H. Hulstijn Department of Second Language Acquisition, University of Amsterdam Volume 3 Appraising Research in Second Language Learning: A practical approach to critical analysis of quantitative research by Graeme Keith Porte Appraising Research in Second Language Learning A practical approach to critical analysis of quantitative research Graeme Keith Porte University of Granada John Benjamins Publishing Company Amsterdam / Philadelphia Dr Graeme Keith Porte is currently Senior Lecturer at the University of Granada in Spain, where he lectures on Second Language Writing and Applied Linguistics Research Design...
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...hkmodergi.org Analysis of surface textures of physiographic features extracted from multiscale digital elevation models via grey level co-occurrence matrix Dinesh Sathyamoorthy* Science & Technology Research Institute for Defence (STRIDE), Ministry of Defence, Malaysia Abstract Volume: 2 Issue: 1 Page: 19 - 28 May 2013 This paper is aimed at employing grey level co-occurrence matrix (GLCM) to analyse the surface textures of physiographic features extracted from multiscale digital elevation models (DEMs). Four GLCM parameters, energy, contrast, autocorrelation and entropy, are computed for horizontal (0°), vertical (90°) and diagonal (45 and 135°) cell pair orientations. For the respective DEMs and physiographic features, varying patterns are observed in the plots of the GLCM parameters due to varying surface profiles and the changes that occur over the scales. Due to the smoothing of the terrain during multiscaling, the features have increasing values of energy and entropy, and decreasing values of contrast and entropy, indicating decreasing roughness. Mountains have the highest roughness as compared to the other features over the scales, while basins have the lowest roughness. For each parameter, similar trends are observed in the plots for the four different cell pair orientations, indicating similar trends of change of surface texture in the different orientations over the scales. However, varying values are observed for the different orientations, depending on textural...
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...Jankovi´, Ivan Mati´, and Nikola Petrovi´ s c c c c Problem-Solving Strategies by Arthur Engel Problems in Analysis by Bernard R. Gelbaum Problems in Real and Complex Analysis by Bernard R. Gelbaum (continued after subject index) Wolfgang Schwarz 40 Puzzles and Problems in Probability and Mathematical Statistics Wolfgang Schwarz Universit¨ t Potsdam a Humanwissenschaftliche Fakult¨ t a Karl-Liebknecht Strasse 24/25 D-14476 Potsdam-Golm Germany wschwarz@uni-potsdam.de Series Editor: Peter Winkler Department of Mathematics Dartmouth College Hanover, NH 03755 USA Peter.winkler@dartmouth.edu ISBN-13: 978-0-387-73511-5 e-ISBN-13: 978-0-387-73512-2 Mathematics Subject Classification (2000): 60-xx Library of Congress Control Number: 2007936604 c 2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts...
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