Download or read book Classical Statistical Analysis Using Jasp written by Christopher P. Halter and published by Independently Published. This book was released on 2018-11-15 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The JASP Guide's purpose is to assist the novice social science and educational researcher in interpreting statistical output data using the JASP Statistical Analysis application. Through the examples and guidance, you will be able to select the statistical test that is appropriate for your data, apply the inferential test to your data, and interpret a statistical test's output table. These analysis methods include Contingency Tables, t-Tests, ANOVA, ANCOVA, Correlation, Linear Regression, and Binomial Logistic Regression. The guide also includes procedures for Reliability and Factor Analysis. The JASP application supports both Frequentist and Bayesian procedures.This guide is part of a three volume series.Volume One: Classical Statistical Analysis Using JASP covers the basic Frequentists analysis methods for both parametric and non-parametric data.Volume Two: Bayesian Statistical Analysis Using JASP covers the basic Bayesian analysis methods for both parametric and non-parametric data.The Complete Guide: Exploring Statistical Analysis Using JASP contains all of the methods, examples, and guidance contained in Volumes One and Two. The Complete Guide covers both Frequentists and Bayesian analysis methods.

Download or read book Bayesian Statistical Analysis Using Jasp written by Christopher P. Halter and published by Independently Published. This book was released on 2018-11-15 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: The JASP Guide's purpose is to assist the novice social science and educational researcher in interpreting statistical output data using the JASP Statistical Analysis application. Through the examples and guidance, you will be able to select the statistical test that is appropriate for your data, apply the inferential test to your data, and interpret a statistical test's output table. These analysis methods include Contingency Tables, t-Tests, ANOVA, ANCOVA, Correlation, Linear Regression, and Binomial Logistic Regression. The guide also includes procedures for Reliability and Factor Analysis. The JASP application supports both Frequentist and Bayesian procedures.This guide is part of a three volume series.Volume One: Classical Statistical Analysis Using JASP covers the basic Frequentists analysis methods for both parametric and non-parametric data.Volume Two: Bayesian Statistical Analysis Using JASP covers the basic Bayesian analysis methods for both parametric and non-parametric data.The Complete Guide: Exploring Statistical Analysis Using JASP contains all of the methods, examples, and guidance contained in Volumes One and Two. The Complete Guide covers both Frequentists and Bayesian analysis methods.

Download or read book Exploring Statistical Analysis Using Jasp written by Christopher P. Halter and published by . This book was released on 2018-11-23 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide is part of a three volume series. Volume One: Classical Statistical Analysis Using JASP covers the basic Frequentists analysis methods for both parametric and non-parametric data. Volume Two: Bayesian Statistical Analysis Using JASP covers the basic Bayesian analysis methods for both parametric and non-parametric data. Volume 3: Exploring Statistical Analysis Using JASP contains all of the methods, examples, and guidance contained in Volumes One and Two, covering both Frequentists and Bayesian analysis methods. The JASP Guide's purpose is to assist the novice social science and educational researcher in interpreting statistical output data using the JASP Statistical Analysis application. Through the examples and guidance, you will be able to select the statistical test that is appropriate for your data, apply the inferential test to your data, and interpret a statistical test's output table. These analysis methods include Contingency Tables, t-Tests, ANOVA, ANCOVA, Correlation, Linear Regression, and Binomial Logistic Regression. The guide also includes procedures for Reliability and Factor Analysis. The JASP application supports both Frequentist and Bayesian procedures.

Download or read book Statistical Power Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-05-13 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.

Download or read book Statistics for the Behavioural Sciences written by Riccardo Russo and published by Psychology Press. This book was released on 2004-08-02 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you find statistics overwhelming and confusing? Have you ever wished for someone to explain the basics in a clear and easy-to-follow style? This accessible textbook gives a step-by-step introduction to all the topics covered in introductory statistics courses for the behavioural sciences, with plenty of examples discussed in depth, based on real psychology experiments utilising the statistical techniques described. Advanced sections are also provided, for those who want to learn a particular topic in more depth. Statistics for the Behavioural Sciences: An Introduction begins with an introduction to the basic concepts, before providing a detailed explanation of basic statistical tests and concepts such as descriptive statistics, probability, the binomial distribution, continuous random variables, the normal distribution, the Chi-Square distribution, the analysis of categorical data, t-tests, correlation and regression. This timely and highly readable text will be invaluable to undergraduate students of psychology, and students of research methods courses in related disciplines, as well as anyone with an interest in the basic concepts and tests associated with statistics in the behavioural sciences.

Download or read book The Fast Guide to Statistical Testing with JASP written by Cole Davis and published by Statistics without Mathematics. This book was released on 2023-06-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics book for beginners, introducing both classical and Bayesian statistics, without formulae. Worked examples are given for each test, suitable for social sciences undergraduates.

Download or read book Modern Statistical Methods for HCI written by Judy Robertson and published by Springer. This book was released on 2016-03-22 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book critically reflects on current statistical methods used in Human-Computer Interaction (HCI) and introduces a number of novel methods to the reader. Covering many techniques and approaches for exploratory data analysis including effect and power calculations, experimental design, event history analysis, non-parametric testing and Bayesian inference; the research contained in this book discusses how to communicate statistical results fairly, as well as presenting a general set of recommendations for authors and reviewers to improve the quality of statistical analysis in HCI. Each chapter presents [R] code for running analyses on HCI examples and explains how the results can be interpreted. Modern Statistical Methods for HCI is aimed at researchers and graduate students who have some knowledge of “traditional” null hypothesis significance testing, but who wish to improve their practice by using techniques which have recently emerged from statistics and related fields. This book critically evaluates current practices within the field and supports a less rigid, procedural view of statistics in favour of fair statistical communication.

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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

Download or read book Statistical Methods For Research Workers written by R a Fisher and published by Gyan Books. This book was released on 2017 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Title 'Encyclopaedia of Dalits in India (Women) written/authored/edited by Sanjay Paswan, Paramanshi Jaideva', published in the year 2002. The ISBN 9788178350325 is assigned to the Hardcover version of this title. This book has total of pp. 415 (Pages). The publisher of this title is Kalpaz Publications. This Book is in English. The subject of this book is Reference / Dictionary / Encyclopaedia / Scheduled Castes / OBC / Minorities / Sociology. Size of the book is.

Download or read book Introduction to Statistical Data Analysis for the Life Sciences written by Claus Thorn Ekstrom and published by CRC Press. This book was released on 2014-11-06 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Hands-On Approach to Teaching Introductory StatisticsExpanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the m

Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Download or read book Introduction to the New Statistics written by Geoff Cumming and published by Routledge. This book was released on 2016-10-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.

Download or read book Doing Meta Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

Download or read book Statistical Power Analysis written by Kevin R. Murphy and published by Routledge. This book was released on 2003-08-01 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a simple and general method for conducting statistical power analysis based on the widely used F statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. Statistical Power Analysis examines the four major applications of power analysis, concentrating on how to determine: *the sample size needed to achieve desired levels of power; *the level of power that is needed in a study; *the size of effect that can be reliably detected by a study; and *sensible criteria for statistical significance. Highlights of the second edition include: a CD with an easy-to-use statistical power analysis program; a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; and a new One-Stop PV Table to serve as a quick reference guide. The book discusses the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. It demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis. Ideal for students and researchers of statistical and research methodology in the social, behavioral, and health sciences who want to know how to apply methods of power analysis to their research.

Download or read book Discovering Statistics Using IBM SPSS Statistics written by Andy Field and published by SAGE. This book was released on 2017-11-03 with total page 2051 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an exciting new look, math diagnostic tool, and a research roadmap to navigate projects, this new edition of Andy Field’s award-winning text offers a unique combination of humor and step-by-step instruction to make learning statistics compelling and accessible to even the most anxious of students. The Fifth Edition takes students from initial theory to regression, factor analysis, and multilevel modeling, fully incorporating IBM SPSS Statistics© version 25 and fascinating examples throughout. SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning. Course cartridges available for Blackboard, Canvas, and Moodle. Andy Field is the award winning author of An Adventure in Statistics: The Reality Enigma and is the recipient of the UK National Teaching Fellowship (2010), British Psychological Society book award (2006), and has been recognized with local and national teaching awards (University of Sussex, 2015, 2016).

Download or read book Doing Bayesian Data Analysis written by John Kruschke and published by Academic Press. This book was released on 2014-11-11 with total page 772 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes' rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business. - Accessible, including the basics of essential concepts of probability and random sampling - Examples with R programming language and JAGS software - Comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) - Coverage of experiment planning - R and JAGS computer programming code on website - Exercises have explicit purposes and guidelines for accomplishment - Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs

Download or read book Informative Hypotheses written by Herbert Hoijtink and published by CRC Press. This book was released on 2011-10-26 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: When scientists formulate their theories, expectations, and hypotheses, they often use statements like: ``I expect mean A to be bigger than means B and C"; ``I expect that the relation between Y and both X1 and X2 is positive"; and ``I expect the relation between Y and X1 to be stronger than the relation between Y and X2". Stated otherwise, they formulate their expectations in terms of inequality constraints among the parameters in which they are interested, that is, they formulate Informative Hypotheses. There is currently a sound theoretical foundation for the evaluation of informative hypotheses using Bayes factors, p-values and the generalized order restricted information criterion. Furthermore, software that is often free is available to enable researchers to evaluate the informative hypotheses using their own data. The road is open to challenge the dominance of the null hypothesis for contemporary research in behavioral, social, and other sciences.