Analysis of Variance via Confidence Intervals PDF Download
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Author: K D Bird
Publisher: SAGE
ISBN: 1847871089
Category : Social Science
Languages : en
Pages : 239
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Book Description
Analysis of variance (ANOVA) constitutes the main set of statistical methods used by students and researchers to analyse data from experiments. This expertly written textbook adopts a pioneering approach to ANOVA with an emphasis on confidence intervals rather than tests of significance. Key features of the book include: · Extensive coverage · Strong emphasis upon practical examples · Web-based links to sample questions and answers Student-focused throughout, it offers a comprehensive introduction to ANOVA using confidence intervals. The chapters have been organized to fit onto a typical lecture programme and is well-structured and practical, invaluable for undergraduates and postgraduate students taking courses in quantitative methods across the social sciences.
Author: K D Bird
Publisher: SAGE
ISBN: 1847871089
Category : Social Science
Languages : en
Pages : 239
Get Book Here
Book Description
Analysis of variance (ANOVA) constitutes the main set of statistical methods used by students and researchers to analyse data from experiments. This expertly written textbook adopts a pioneering approach to ANOVA with an emphasis on confidence intervals rather than tests of significance. Key features of the book include: · Extensive coverage · Strong emphasis upon practical examples · Web-based links to sample questions and answers Student-focused throughout, it offers a comprehensive introduction to ANOVA using confidence intervals. The chapters have been organized to fit onto a typical lecture programme and is well-structured and practical, invaluable for undergraduates and postgraduate students taking courses in quantitative methods across the social sciences.
Author: K D Bird
Publisher: SAGE
ISBN: 9780761963578
Category : Social Science
Languages : en
Pages : 244
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Book Description
Analysis of variance - ANOVA - constitutes the main set of statistical methods through which undergraduate and postgraduate students carry out multivariate analysis. This textbook adopts an innovative approach to ANOVA, placing emphasis on confidence intervals rather than tests of significance.
Author: Burdick
Publisher: CRC Press
ISBN: 9780824786441
Category : Mathematics
Languages : en
Pages : 238
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Book Description
Summarizes information scattered in the technical literature on a subject too new to be included in most textbooks, but which is of interest to statisticians, and those who use statistics in science and education, at an advanced undergraduate or higher level. Overviews recent research on constructin
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309045991
Category : Computers
Languages : en
Pages : 99
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Book Description
This book presents guidelines for the development and evaluation of statistical software designed to ensure minimum acceptable statistical functionality as well as ease of interpretation and use. It consists of the proceedings of a forum that focused on three qualities of statistical software: richnessâ€"the availability of layers of output sophistication, guidanceâ€"how the package helps a user do an analysis and do it well, and exactnessâ€"determining if the output is "correct" and when and how to warn of potential problems.
Author: Douglas Altman
Publisher: John Wiley & Sons
ISBN: 1118702506
Category : Medical
Languages : en
Pages : 322
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Book Description
This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
Author: Robert K. Leik
Publisher: SAGE Publications
ISBN: 1452250359
Category : Social Science
Languages : en
Pages : 209
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Book Description
Why is this Book a Useful Supplement for Your Statistics Course? Most core statistics texts cover subjects like analysis of variance and regression, but not in much detail. This book, as part of our Series in Research Methods and Statistics, provides you with the flexibility to cover ANOVA more thoroughly, but without financially overburdening your students.
Author: Ronald Christensen
Publisher: CRC Press
ISBN: 9780412062919
Category : Mathematics
Languages : en
Pages : 608
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Book Description
This text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.
Author: Neil J. Salkind
Publisher: SAGE
ISBN: 1412961270
Category : Philosophy
Languages : en
Pages : 1779
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Book Description
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
Author: Daniel B Wright
Publisher: SAGE
ISBN: 1446242781
Category : Social Science
Languages : en
Pages : 250
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Book Description
′This engagingly written and nicely opinionated book is a blend of friendly introduction and concisely applicable detail. No-one can recall every statistical formula, but if they have this book they will know where to look′ - Professor Jon May, University of Plymouth ′This is one of the best books I have come across for teaching introductory statistics. The illustrative examples are engaging and often humorous and the explanations of ′difficult′ concepts are written in a wonderfully clear and intuitive way′ - Nick Allum, University of Essex Selected as an Outstanding Academic Title by Choice Magazine, January 2010 First (and Second) Steps in Statistics, Second Edition provides a clear and concise introduction to the main statistical procedures used in the social and behavioural sciences and is perfect for the statistics student starting their journey. The rationale and procedure for analyzing data are presented through exciting examples with an emphasis on understanding rather than computation. It is ideally suited for introductory courses in statistics given its gentle beginning, yet progressive treatment of topics. In addition to descriptive statistics, graphs, t-tests, oneway ANOVAs, Chi-square, and simple linear regression, this Second Edition now includes some new, more advanced topic areas as well as a host of additional examples to help students confidently progress through their studies and apply the techniques in lab work, reports and research projects. Key features of this new edition: - the reoganization of the first three chapters giving more attention to univariate statistics and providing more examples to work through at this level - more advanced ′second step′ content has been added on factorial ANOVA and multiple regression - the robust methods chapter from the first edition is now spread throughout the book, and is linked with common teaching practices. - many more examples have been added to enhance the book′s practical potential. - a host of exercises as well as further reading sections at the end of every chapter. An accompanying Web page includes information for each chapter using the statistical packages SPSS and R.
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
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Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
