Probability & Statistical Concepts:an Introduction PDF Download

Author:
Publisher: Rex Bookstore, Inc.
ISBN: 9789712322228
Category :
Languages : en
Pages : 226

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Author: Richard G Lomax
Publisher: Routledge
ISBN: 1136490124
Category : Psychology
Languages : en
Pages : 1259

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Book Description
This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance. This edition features more explanation to increase understanding of the concepts. Only crucial equations are included. In addition to updating throughout, the new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. More on computing confidence intervals and conducting power analyses using G*Power. Many more SPSS screenshots to assist with understanding how to navigate SPSS and annotated SPSS output to assist in the interpretation of results. Extended sections on how to write-up statistical results in APA format. New learning tools including chapter-opening vignettes, outlines, and a list of key concepts, many more examples, tables, and figures, boxes, and chapter summaries. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website that features PowerPoint slides, answers to the even-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets that can be used in SPSS and other packages, and more. Each chapter begins with an outline, a list of key concepts, and a vignette related to those concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides instructions for how to run SPSS, including annotated output, and tips to develop an APA style write-up. Useful tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. 'Stop and Think' boxes provide helpful tips for better understanding the concepts. Each chapter includes computational, conceptual, and interpretive problems. The data sets used in the examples and problems are provided on the web. Answers to the odd-numbered problems are given in the book. The first five chapters review descriptive statistics including ways of representing data graphically, statistical measures, the normal distribution, and probability and sampling. The remainder of the text covers inferential statistics involving means, proportions, variances, and correlations, basic and advanced analysis of variance and regression models. Topics not dealt with in other texts such as robust methods, multiple comparison and nonparametric procedures, and advanced ANOVA and multiple and logistic regression models are also reviewed. Intended for one- or two-semester courses in statistics taught in education and/or the behavioral sciences at the graduate and/or advanced undergraduate level, knowledge of statistics is not a prerequisite. A rudimentary knowledge of algebra is required.

Author: Walter A. Rosenkrantz
Publisher: CRC Press
ISBN: 158488813X
Category : Mathematics
Languages : en
Pages : 680

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Book Description
Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create

Author: Richard G. Lomax
Publisher: Psychology Press
ISBN: 9780805827491
Category : Mathematics
Languages : en
Pages : 520

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Book Description
This book provides comprehensive coverage so that it can be used in a single- or two-course sequence in statistics. It provides greater flexibility because it contains many topics not dealt with in other introductory texts. Its conceptual, intuitive approach allows for concepts to be easily stated and related to real-life examples. Throughout the text the author demonstrates how many statistical concepts can be related to one another. Unlike other texts, this book includes the following topics: * skewness and kurtosis measures; * inferences about two dependent proportions and two independent means with unequal variances; * homogeneity of variance tests; * layout of the data in ANOVA models; * the ANOVA linear model; * a wide variety of multiple comparison procedures; * significance tests in multiple linear regression; and * extensive discussion of assumptions and how to deal with assumption violations. Numerous tables and figures help illustrate concepts and present examples within the text. An extensive bibliography is included. A number of pedagogical devices are included to increase the reader's conceptual understanding of statistics: chapter outlines; list of key concepts for each chapter; chapter objectives; numerous realistic examples; summary tables of statistical assumptions; extensive references; and end of chapter conceptual and computational problems. An instructor's manual is available containing answers to all of the problems, as well as a collection of statistical humor designed to be an instructional aid. This book is intended for introductory statistics courses for students in education and behavioral sciences.

Author: Richard G. Lomax
Publisher: Routledge
ISBN: 113649006X
Category : Psychology
Languages : en
Pages : 532

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Book Description
Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts, 3rd ed. Designed for the second course in statistics, it is one of the few texts that focuses just on intermediate statistics. The book highlights how statistics work and what they mean to better prepare students to analyze their own data and interpret SPSS and research results. As such it offers more coverage of non-parametric procedures used when standard assumptions are violated since these methods are more frequently encountered when working with real data. Determining appropriate sample sizes is emphasized throughout. Only crucial equations are included. The new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. Much more on computing confidence intervals and conducting power analyses using G*Power. All new SPSS version 19 screenshots to help navigate through the program and annotated output to assist in the interpretation of results. Sections on how to write-up statistical results in APA format and new templates for writing research questions. New learning tools including chapter-opening vignettes, outlines, a list of key concepts, "Stop and Think" boxes, and many more examples, tables, and figures. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website with Power Points, answers to the even-numbered problems, detailed solutions to the odd-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets. Each chapter begins with an outline, a list of key concepts, and a research vignette related to the concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides tips for how to run SPSS and develop an APA style write-up. Tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Each chapter includes computational, conceptual, and interpretive problems. Answers to the odd-numbered problems are provided. The SPSS data sets that correspond to the book’s examples and problems are available on the web. The book covers basic and advanced analysis of variance models and topics not dealt with in other texts such as robust methods, multiple comparison and non-parametric procedures, and multiple and logistic regression models. Intended for courses in intermediate statistics and/or statistics II taught in education and/or the behavioral sciences, predominantly at the master's or doctoral level. Knowledge of introductory statistics is assumed.

Author: F.M. Dekking
Publisher: Springer Science & Business Media
ISBN: 1846281687
Category : Mathematics
Languages : en
Pages : 488

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Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Author: Joseph Lawson Hodges
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 400

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Author: Michael O. Finkelstein
Publisher: Springer Science & Business Media
ISBN: 0387875018
Category : Law
Languages : en
Pages : 174

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Book Description
When as a practicing lawyer I published my ?rst article on statistical evidence in 1966, the editors of the Harvard Law Review told me that a mathematical equa- 1 tion had never before appeared in the review. This hardly seems possible - but if they meant a serious mathematical equation, perhaps they were right. Today all that has changed in legal academia. Whole journals are devoted to scienti?c methods in law or empirical studies of legal institutions. Much of this work involves statistics. Columbia Law School, where I teach, has a professor of law and epidemiology and other law schools have similar “law and” professorships. Many offer courses on statistics (I teach one) or, more broadly, on law and social science. The same is true of practice. Where there are data to parse in a litigation, stat- ticians and other experts using statistical tools now frequently testify. And judges must understand them. In 1993, in its landmark Daubert decision, the Supreme Court commanded federal judges to penetrate scienti?c evidence and ?nd it “re- 2 liable” before allowing it in evidence. It is emblematic of the rise of statistics in the law that the evidence at issue in that much-cited case included a series of epidemiological studies. The Supreme Court’s new requirement made the Federal Judicial Center’s Reference Manual on Scienti?c Evidence, which appeared at about the same time, a best seller. It has several important chapters on statistics.

Author: Cheryl Ann Willard
Publisher: Routledge
ISBN: 0429523157
Category : Psychology
Languages : en
Pages : 350

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Book Description
Statistical Methods: An Introduction to Basic Statistical Concepts and Analysis, Second Edition is a textbook designed for students with no prior training in statistics. It provides a solid background of the core statistical concepts taught in most introductory statistics textbooks. Mathematical proofs are deemphasized in favor of careful explanations of statistical constructs. The text begins with coverage of descriptive statistics such as measures of central tendency and variability, then moves on to inferential statistics. Transitional chapters on z-scores, probability, and sampling distributions pave the way to understanding the logic of hypothesis testing and the inferential tests that follow. Hypothesis testing is taught through a four-step process. These same four steps are used throughout the text for the other statistical tests presented including t tests, one- and two-way ANOVAs, chi-square, and correlation. A chapter on nonparametric tests is also provided as an alternative when the requirements cannot be met for parametric tests. Because the same logical framework and sequential steps are used throughout the text, a consistency is provided that allows students to gradually master the concepts. Their learning is enhanced further with the inclusion of "thought questions" and practice problems integrated throughout the chapters. New to the second edition: Chapters on factorial analysis of variance and non-parametric techniques for all data Additional and updated chapter exercises for students to test and demonstrate their learning Full instructor resources: test bank questions, Powerpoint slides, and an Instructor Manual

Author: Narayanaswamy Balakrishnan
Publisher: John Wiley & Sons
ISBN: 1118548558
Category : Mathematics
Languages : en
Pages : 548

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Book Description
INTRODUCTION TO PROBABILITY Discover practical models and real-world applications of multivariate models useful in engineering, business, and related disciplines In Introduction to Probability: Multivariate Models and Applications, a team of distinguished researchers delivers a comprehensive exploration of the concepts, methods, and results in multivariate distributions and models. Intended for use in a second course in probability, the material is largely self-contained, with some knowledge of basic probability theory and univariate distributions as the only prerequisite. This textbook is intended as the sequel to Introduction to Probability: Models and Applications. Each chapter begins with a brief historical account of some of the pioneers in probability who made significant contributions to the field. It goes on to describe and explain a critical concept or method in multivariate models and closes with two collections of exercises designed to test basic and advanced understanding of the theory. A wide range of topics are covered, including joint distributions for two or more random variables, independence of two or more variables, transformations of variables, covariance and correlation, a presentation of the most important multivariate distributions, generating functions and limit theorems. This important text: Includes classroom-tested problems and solutions to probability exercises Highlights real-world exercises designed to make clear the concepts presented Uses Mathematica software to illustrate the text’s computer exercises Features applications representing worldwide situations and processes Offers two types of self-assessment exercises at the end of each chapter, so that students may review the material in that chapter and monitor their progress Perfect for students majoring in statistics, engineering, business, psychology, operations research and mathematics taking a second course in probability, Introduction to Probability: Multivariate Models and Applications is also an indispensable resource for anyone who is required to use multivariate distributions to model the uncertainty associated with random phenomena.