This book began many years ago as course notes for students at the University of Bath, and later at the University of Kent.

Author: G. Barrie Wetherill

Publisher: Springer

ISBN: UOM:39015000244437

Category: Juvenile Nonfiction

Page: 418

View: 837

This book began many years ago as course notes for students at the University of Bath, and later at the University of Kent. Students used draft versions of the chapters, which were consequently revised. Second and third year students, as well as those taking MSc courses have used selections of the chapters. In particular, Chapters I to 7 (only) have been the basis of a very successful second-year course, the more difficult sections being omitted. The aims of this particular course were:- (a) to cover some interesting and useful applications of statistics with an emphasis on applications, but with really adequate theory; (b) to lay the foundations for interesting third-year courses; (c) to tie up with certain areas of pure mathematics and numerical analysis. 2 Students will find Chapter I a useful means of revising the t, X and F procedures, which is material assumed in this text, see Section 1.1. Later sections of Chapter I cover robustness and can be omitted by second-year students or at a first reading. Chapter 2 introduces some simple statistical models, so that the discussion of later chapters is more meaningful.

4 IMPLEMENTING STATISTICAL PROCEDURES So far we have succeeded in setting up and saving a data file on your PC . Now we must learn how to use the STATISTICA modules and procedures to produce statistical analyses and outputs for us .

Author: Rob Van Den Honert

Publisher: Juta and Company Ltd

ISBN: 1919713387

Category: Business & Economics

Page: 450

View: 830

This text is aimed at commerce and social science students who have already completed a first semester course in mathematics and applied statistics.

[AN, III] Snedecor, G.W. & Haber, E.S. (1946) 'Statistical methods for an incomplete experiment on a perennial crop', Biometrics, 2,61–7, [AN,II] Snee, R.D. (1971) 'Design and analysis of mixture ...

Author: G. Barrie Wetherill

Publisher: Springer Science & Business Media

ISBN: 9789400958364

Category: Science

Page: 392

View: 761

This book began many years ago as course notes for students at the University of Bath, and later at the University of Kent. Students used draft versions of the chapters, which were consequently revised. Second and third year students, as well as those taking MSc courses have used selections of the chapters. In particular, Chapters I to 7 (only) have been the basis of a very successful second-year course, the more difficult sections being omitted. The aims of this particular course were:- (a) to cover some interesting and useful applications of statistics with an emphasis on applications, but with really adequate theory; (b) to lay the foundations for interesting third-year courses; (c) to tie up with certain areas of pure mathematics and numerical analysis. 2 Students will find Chapter I a useful means of revising the t, X and F procedures, which is material assumed in this text, see Section 1.1. Later sections of Chapter I cover robustness and can be omitted by second-year students or at a first reading. Chapter 2 introduces some simple statistical models, so that the discussion of later chapters is more meaningful.

This booklet contains hints to the solutions and answers where necessary, of the exercises contained in 'Intermediate Statistical Methods' by G. Barrie Wetherill. The following principles have been adopted in dealing with the answers.

Author: G. Barrie Wetherill

Publisher: Springer Science & Business Media

ISBN: 9789401160308

Category: Science

Page: 74

View: 756

This booklet contains hints to the solutions and answers where necessary, of the exercises contained in 'Intermediate Statistical Methods' by G. Barrie Wetherill. The following principles have been adopted in dealing with the answers. (1) In some cases the answer is the drawing of a graph, and this has been omitted. (2) In many numerical exercises a considerable amount of 'data snooping', plotting of residuals, etc. should follow the main ~sis. The inclusion of this material would make the answer booklet far too long. (3) In some cases there is a readily available reference from which the answer can be ob~ained, in which case reference has been made to this. It is not necessary to work through every exercise , but it should be recognised that the exercises are an integral part of the main text, and a comprehensive grasp of the subj ect cannot be obtained without attempting a substantial proportion of them. It is hoped that this booklet will be of assistance in pointing the way, and providing a check on the more vital calculations. The importance of numerical exercises should be stressed, and it is here that Appendix B is of importance. There is abundant material available there in many different fields of application. Currently we are in the process of mounting a form of Appendix B on a computer, together with accessing programs.

Ordinal DATA: These types of DATA are intermediate between nominal and continuous. ... Some statistics sources classify DATA types further as ratio, interval, ordinal, and nominal. ... 38 Understanding Advanced Statistical Methods.

Author: Peter Westfall

Publisher: CRC Press

ISBN: 9781466512115

Category: Mathematics

Page: 569

View: 733

Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Alessandra Coli and Francesca Tartamella Abstract National accounts statistics are the result of the integration of several ... The first method measures GDP as the value of goods and services produced by the nation, net of intermediate ...

Author: Agostino Di Ciaccio

Publisher: Springer Science & Business Media

ISBN: 9783642210365

Category: Mathematics

Page: 464

View: 610

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Various statistical methods have been used in information science research . These range from basic methods , such as those discussed in the preceding chapters , to more advanced ones . There is no strict definition dividing basic ...

Author: Liwen Vaughan

Publisher: Information Today, Inc.

ISBN: 1573871109

Category: Business & Economics

Page: 248

View: 331

For most of us, "painless" is not the word that comes to mind when we think of statistics, but author and educator Liwen Vaughan wants to change that. In this unique and useful book, Vaughan clearly explains the statistical methods used in information science research, focusing on basic logic rather than mathematical intricacies. Her emphasis is on the meaning of statistics, when and how to apply them, and how to interpret the results of statistical analysis. Through the use of real-world examples, she shows how statistics can be used to improve services, make better decisions, and conduct more effective research. Whether you are doing statistical analysis or simply need to better understand the statistics you encounter in professional literature and the media, this book will be a valuable addition to your personal toolkit. Includes more than 80 helpful figures and tables, 7 appendices, bibliography, index.

Author: Mervyn G. MarasinghePublish On: 2008-12-10

This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level.

Author: Mervyn G. Marasinghe

Publisher: Springer Science & Business Media

ISBN: 9780387773728

Category: Mathematics

Page: 558

View: 729

This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Chapter 4 presents one method of assessing validity; including exploratory factor analysis and principal components analysis. Again, these statistical methods are often used to prepare your data so it will be ready to use to help answer ...

Author: Nancy L. Leech

Publisher: Routledge

ISBN: 9781136334931

Category: Psychology

Page: 382

View: 896

Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design; perform intermediate statistics, including multivariate statistics; interpret output; and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data; how to determine whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic analysis; how to compute and interpret post-hoc power; and an overview of basic statistics for those who need a review. Unique chapters on multilevel linear modeling; multivariate analysis of variance (MANOVA); assessing reliability of data; multiple imputation; mediation, moderation, and canonical correlation; and factor analysis are provided. SPSS syntax with output is included for those who prefer this format. The new edition features: • IBM SPSS version 22; although the book can be used with most older and newer versions • New discusiion of intraclass correlations (Ch. 3) • Expanded discussion of effect sizes that includes confidence intervals of effect sizes (ch.5) • New information on part and partial correlations and how they are interpreted and a new discussion on backward elimination, another useful multiple regression method (Ch. 6) • New chapter on how to use a variable as a mediator or a moderator (ch. 7) • Revised chapter on multilevel and hierarchical linear modeling (ch. 12) • A new chapter (ch. 13) on multiple imputation that demonstrates how to deal with missing data • Updated web resources for instructors including PowerPoint slides and answers to interpretation questions and extra problems and for students, data sets, chapter outlines, and study guides. IBM SPSS for Intermediate Statistics, Fifth Edition provides helpful teaching tools: • all of the key SPSS windows needed to perform the analyses • outputs with call-out boxes to highlight key points • interpretation sections and questions to help students better understand and interpret the output • extra problems with realistic data sets for practice using intermediate statistics • Appendices on how to get started with SPSS, write research questions, and basic statistics. An ideal supplement for courses in either intermediate/advanced statistics or research methods taught in departments of psychology, education, and other social, behavioral, and health sciences. This book is also appreciated by researchers in these areas looking for a handy reference for SPSS

Psychological Methods, 10, 227–254. doi:10.1037/1082989x.10.2.227 Gasparrini, A., Armstrong, B., & Kenward, M. G. (2012). Multivariate meta‐analysis for non‐linear and other multi‐parameter associations. Statistics in Medicine, 31, ...

Author: Nikos Ntoumanis

Publisher: John Wiley & Sons

ISBN: 9781118962053

Category: Medical

Page: 312

View: 387

"Ntoumanis and Myers have done sport and exercise science researchers and students a tremendous service in producing An Introduction to Intermediate and Advanced Statistical Analyses for Sport and Exercise Scientists. This book has an outstanding compilation of comprehensible chapters dealing with the important concepts and technical minutia of the statistical analyses that sport and exercise science scholars use (or should be using!) in their efforts to conduct meaningful research in the field. It is a resource that all sport and exercise scientists and their students should have on their book shelves." —Robert Eklund, School of Sport, University of Stirling, UK "Motivating, to have a statistics text devoted to enabling researchers studying sport and exercise science to apply the most sophisticated analytical techniques to their data. Authors hit the mark between using technical language as necessary and user-friendly terms or translations to keep users encouraged. Text covers traditional and well-used tools but also less common and more complex tools, but always with familiar examples to make their explanations come alive. As a dynamic systems theorist and developmentalist, I would love to see more researchers in my area create study designs that would enable the use of tools outlined here, such as multilevel structural equation modeling (MSEM) or mediation & moderation analyses, to uncover cascades of relations among subsystems contributing to motor performance, over time. This text can facilitate that outcome." —Beverly D. Ulrich, School of Kinesiology, University of Michigan, USA "The domain of quantitative methods is constantly evolving and expanding. This means that there is tremendous pressure on researchers to stay current, both in terms of best practices and improvements in more traditional methods as well as increasingly complex new methods. With this volume Ntoumanis and Myers present a nice cross-section of both, helping sport and exercise science researchers to address old questions in better ways, and, even more excitingly, to address new questions entirely. I have no doubt that this volume will quickly become a lovingly dog-eared companion for students and researchers, helping them to continue to move the field forward." —Gregory R. Hancock, University of Maryland and Center for Integrated Latent Variable Research (CILVR), USA