Statistical Inference

Author: Michael J. Panik
Publisher: John Wiley & Sons
ISBN: 1118309804
Format: PDF, ePub, Mobi
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A concise, easily accessible introduction to descriptiveand inferential techniques Statistical Inference: A Short Course offers a concisepresentation of the essentials of basic statistics for readersseeking to acquire a working knowledge of statistical concepts,measures, and procedures. The author conducts tests on the assumption of randomness andnormality, provides nonparametric methods when parametricapproaches might not work. The book also explores how to determinea confidence interval for a population median while also providingcoverage of ratio estimation, randomness, and causality. To ensurea thorough understanding of all key concepts, StatisticalInference provides numerous examples and solutions along withcomplete and precise answers to many fundamental questions,including: How do we determine that a given dataset is actually a randomsample? With what level of precision and reliability can a populationsample be estimated? How are probabilities determined and are they the same thing asodds? How can we predict the level of one variable from that ofanother? What is the strength of the relationship between twovariables? The book is organized to present fundamental statisticalconcepts first, with later chapters exploring more advanced topicsand additional statistical tests such as Distributional Hypotheses,Multinomial Chi-Square Statistics, and the Chi-Square Distribution.Each chapter includes appendices and exercises, allowing readers totest their comprehension of the presented material. Statistical Inference: A Short Course is an excellentbook for courses on probability, mathematical statistics, andstatistical inference at the upper-undergraduate and graduatelevels. The book also serves as a valuable reference forresearchers and practitioners who would like to develop furtherinsights into essential statistical tools.

Christian and Humanist Foundations for Statistical Inference

Author: Andrew M. Hartley
Publisher: Wipf and Stock Publishers
ISBN: 1556355491
Format: PDF, Mobi
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The Philosophy of the Law Idea (PLI) analyzes the manner in which religious beliefs control scientific theorizing. Religious beliefs control philosophical overviews of reality. Overviews of reality, also called ontologies, try to discover and disclose the essential nature of reality. They are concerned with what kinds of things exist and with the connections between the various types of properties and laws in human experience. Among such overviews are the biblically consistent overview provided by the PLI and certain humanist mathematicist and subjectivist overviews. The science of statistical inference seeks to evaluate the credibility of scientific hypotheses given empirical data. This essay reviews various popular paradigms, or systems of theories, concerning the ways that credibility may be evaluated, and identifies some ways that these religiously controlled overviews of reality have, in turn, controlled statistical paradigms. In particular, one paradigm harmonizes with the PLI's overview; another, with the subjectivist overview; and two others, with the mathematicist overview.

Statistical Inference

Author: Murray Aitkin
Publisher: CRC Press
ISBN: 1420093444
Format: PDF, ePub
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Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing. After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It presents Bayesian versions of one- and two-sample t-tests, along with the corresponding normal variance tests. The author then thoroughly discusses the use of the multinomial model and noninformative Dirichlet priors in "model-free" or nonparametric Bayesian survey analysis, before covering normal regression and analysis of variance. In the chapter on binomial and multinomial data, he gives alternatives, based on Bayesian analyses, to current frequentist nonparametric methods. The text concludes with new goodness-of-fit methods for assessing parametric models and a discussion of two-level variance component models and finite mixtures. Emphasizing the principles of Bayesian inference and Bayesian model comparison, this book develops a unique methodology for solving challenging inference problems. It also includes a concise review of the various approaches to inference.

Statistical Inference

Author: Tadeusz Bromek
Publisher: Springer Science & Business Media
ISBN: 9400905750
Format: PDF, ePub, Docs
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Use and misuse of statistics seems to be the signum temporis of past decades. But nowadays this practice seems slowly to be wearing away, and common sense and responsibility recapturing their position. It is our contention that little by little statistics should return to its starting point, i.e., to formalizing and analyzing empirical phenomena. This requires the reevalu ation of many traditions and the rejection of many myths. We hope that our book would go some way towards this aim. We show the sharp conflict between what is needed and what is feasible. Moreover, we show how slender are the links between theory and practice in statistical inference, links which are sometimes no more than mutual inspiration. In Part One we present the consecutive stages of formalization of statistical problems, i.e., the description of the experiment, the presentation of the aim of the investigation, and of the constraints put upon the decision rules. We stress the fact that at each of these stages there is room for arbitrariness. We prove that the links between the real problem and its formal counterpart are often so weak that the solution of the formal problem may have no rational interpretation at the practical level. We give a considerable amount of thought to the reduction of statistical problems.

Applied Statistics

Author: Franklin A. Graybill
Publisher:
ISBN: 9780136214670
Format: PDF, ePub
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Unique in approach, this practical introduction to statistical inference 1) uses only college algebra, 2) gets into inference within the first 10 pages using popular examples that students encounter every day in newspapers and on television, and 3) emphasizes and covers statistical inference for population proportions in much greater depth than other texts at this level. It features an abundance of examples, problems, and clear computational procedures, and provides a brief introduction to Minitab - with sample data, (on disk) commands, macros (on disk), and printed output. *Uses only college algebra throughout. *Delays coverage of the mean and normal distribution until Chs. 5 and 6, respectively, and focuses first on the basic ideas of statistical inference. *Introduces statistical inference using a proportion - a simple, easily-understood concept that students will see in newspapers, magazines, and on television almost every week. *Features examples, problems, and exercises that do not require a knowledge of any special discipline and that use data based on 'real appearing' studies. *Contains a short introduction to the computing package Minitab (in an appendix), and, throughout

Core Statistics

Author: Simon Wood
Publisher: Cambridge University Press
ISBN: 1107071054
Format: PDF, Docs
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Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Introduction to Quantitative Methods in Business

Author: Bharat Kolluri
Publisher: John Wiley & Sons
ISBN: 1119220971
Format: PDF, ePub, Docs
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A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft® Office Excel® applications used to guide business decision making Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® provides guidance to assessing real-world data sets using Excel. The book presents a balanced approach to the mathematical tools and techniques with applications used in the areas of business, finance, economics, marketing, and operations. The authors begin by establishing a solid foundation of basic mathematics and statistics before moving on to more advanced concepts. The first part of the book starts by developing basic quantitative techniques such as arithmetic operations, functions and graphs, and elementary differentiations (rates of change), and integration. After a review of these techniques, the second part details both linear and nonlinear models of business activity. Extensively classroom-tested, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® also includes: Numerous examples and practice problems that emphasize real-world business quantitative techniques and applications Excel-based computer software routines that explore calculations for an assortment of tasks, including graphing, formula usage, solving equations, and data analysis End-of-chapter sections detailing the Excel applications and techniques used to address data and solutions using large data sets A companion website that includes chapter summaries, Excel data sets, sample exams and quizzes, lecture slides, and an Instructors’ Solutions Manual Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® is an excellent textbook for undergraduate-level courses on quantitative methods in business, economics, finance, marketing, operations, and statistics. The book is also an ideal reference for readers with little or no quantitative background who require a better understanding of basic mathematical and statistical concepts used in economics and business. Bharat Kolluri, Ph.D., is Professor of Economics in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include econometrics, business statistics, quantitative decision making, applied macroeconomics, applied microeconomics, and corporate finance. Michael J. Panik, Ph.D., is Professor Emeritus in the Department of Economics, Finance, and Insurance at the University of Hartford. He has served as a consultant to the Connecticut Department of Motor Vehicles as well as to a variety of health care organizations. In addition, Dr. Panik is the author of numerous books, including Growth Curve Modeling: Theory and Applications and Statistical Inference: A Short Course, both published by Wiley. Rao N. Singamsetti, Ph.D., is Associate Professor in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include the status of war on poverty in the United States since the 1960s and forecasting foreign exchange rates using econometric methods.