Statistics for Sports and Exercise Science

A Practical Approach
Author: John Newell,Tom Aitchison,Stanley Grant
Publisher: Routledge
ISBN: 1317904184
Category: Sports & Recreation
Page: 440
View: 6211
Statistics in Sport and Exercise Science assumes no prior knowledge of statistics and uses real-life case studies to introduce the importance of statistics in sport and exercise science. Statistical tests and techniques are described here in a friendly and easy-to-understand manner, giving you the confidence to analyses data and complete your own statistical studies.

Statistics for Sport and Exercise Studies

An Introduction
Author: Peter O'Donoghue
Publisher: Taylor & Francis
ISBN: 1136479279
Category: Mathematics
Page: 416
View: 1485
Statistics for Sport and Exercise Studies guides the student through the full research process, from selecting the most appropriate statistical procedure, to analysing data, to the presentation of results, illustrating every key step in the process with clear examples, case-studies and data taken from real sport and exercise settings. Every chapter includes a range of features designed to help the student grasp the underlying concepts and relate each statistical procedure to their own research project, including definitions of key terms, practical exercises, worked examples and clear summaries. The book also offers an in-depth and practical guide to using SPSS in sport and exercise research, the most commonly used data analysis software in sport and exercise departments. In addition, a companion website includes more than 100 downloadable data sets and work sheets for use in or out of the classroom, full solutions to exercises contained in the book, plus over 1,300 PowerPoint slides for use by tutors and lecturers. Statistics for Sport and Exercise Studies is a complete, user-friendly introduction to the use of statistical tests, techniques and procedures in sport, exercise and related subjects. Visit the companion website at:

Basic Biostatistics for Geneticists and Epidemiologists

A Practical Approach
Author: Robert C. Elston,William Johnson
Publisher: John Wiley & Sons
ISBN: 0470024917
Category: Medical
Page: 384
View: 5727
Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful Essentials of Biostatistics has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures. This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes’ theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text. Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.

Statistics for the Health Sciences

A Non-Mathematical Introduction
Author: Christine Dancey,John Reidy,Richard Rowe
Publisher: SAGE
ISBN: 1446291235
Category: Social Science
Page: 584
View: 5280
Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae. The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings. Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include: • multiple choice questions for both student and lecturer use • full Powerpoint slides for lecturers • practical exercises using SPSS • additional practical exercises using SAS and R This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences.

Statistics for Nursing: A Practical Approach

Author: Heavey
Publisher: Jones & Bartlett Learning
ISBN: 1284142019
Category: Medical
Page: 302
View: 8069
Statistics for Nursing: A Practical Approach, Third Edition is designed in accordance with the Conversation Theory of Gordon Pask and presents the complicated topic of statistics in an understandable manner for entry level nurses

Measurement and Evaluation in Physical Education and Exercise Science

Author: Alan C. Lacy,Skip M. Williams
Publisher: Routledge
ISBN: 1315312719
Category: Education
Page: 462
View: 623
The eighth edition of Measurement and Evaluation in Physical Education and Exercise Science, now published in paperback and hardback, offers students a clear and practical guide to best practice for measurement and evaluation in school- and nonschool-based physical activity programs. Written by two academics with backgrounds in physical education teacher education (PETE), the book emphasizes the link between theory and practice and reflects the most recent changes in national physical education programs. It covers a full range of introductory topics, including current trends in measurement and evaluation, program development, statistics, test selection, and an expanded chapter on alternative assessment, before introducing: • measurement for health-related physical fitness • measurement for psychomotor skills • measurement for cognitive knowledge • measurement for affective behaviors • grading • self-evaluation. Each chapter features learning aids such as objectives, key terms, practical applications, and review questions, while an appendix offers in-depth Excel assignments. Offering a full companion website featuring an instructor’s manual, lecture slides, and a test bank, Measurement and Evaluation in Physical Education and Exercise Science is a complete resource for instructors and students, alike. It is an essential text for students in measurement and evaluation classes as part of a degree program in physical education, exercise science or kinesiology, and a valuable reference for practitioners seeking to inform their professional practice.

Practical Statistics for Nursing and Health Care

Author: Jim Fowler,Phil Jarvis,Mel Chevannes
Publisher: John Wiley & Sons
ISBN: 111868561X
Category: Science
Page: 400
View: 1193
Nursing is a growing area of higher education, in which an introduction to statistics is an essential component. There is currently a gap in the market for a 'user-friendly' book which is contextulised and targeted for nursing. Practical Statistics for Nursing and Health Care introduces statistical techniques in such a way that readers will easily grasp the fundamentals to enable them to gain the confidence and understanding to perform their own analysis. It also provides sufficient advice in areas such as clinical trials and epidemiology to enable the reader to critically appraise work published in journals such as the Lancet and British Medical Journal. * Covers all basic statistical concepts and tests * Is user-friendly - avoids excessive jargon * Includes relevant examples for nurses, including case studies and data sets * Provides information on further reading * Starts from first principles and progresses step by step * Includes 'advice on' sections for all of the tests described

Statistics for the Social Sciences

Author: R. Mark Sirkin
Publisher: SAGE
ISBN: 9781412905466
Category: Mathematics
Page: 610
View: 2585
Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fear them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained.

Applied Statistics for the Social and Health Sciences

Author: Rachel A. Gordon
Publisher: Routledge
ISBN: 0415875366
Category: Mathematics
Page: 742
View: 7456
Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them. This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature thorough integration of teaching statistical theory with teaching data processing and analysis teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set. This book is for a two-semester course. For a one-semester course, see

Practical Skills in Sport and Exercise Science

Author: Peter Reaburn,Ben Dascombe,Rob Reed,Jonathan Weyers,Allan Jones
Publisher: Pearson Higher Ed
ISBN: 1408203804
Category: Science
Page: 432
View: 6537
If you are studying exercise and sports science, or a related course, then this book will be an indispensable companion throughout your entire degree programme. This ‘one-stop’ text will guide you through the wide range of practical, analytical and data handling skills that you will need during your undergraduate and/or postgraduate studies. It will also give you a solid grounding in the wider transferable skills such as teamwork, using information technology, communicating information and study skills. Practical Skills in Exercise and Sports Science provides an easy-to-read guide to help you develop the skills you need to succeed. It explains the essential elements of practical techniques and procedures in a step-by-step manner to help you understand their application in the context of exercise and sports science. This text’s unique and comprehensive coverage includes: general advice on practical work; measuring techniques; field tests; statistical techniques; analysis and presentation of data; and study skills.

Bayesian Logical Data Analysis for the Physical Sciences

A Comparative Approach with Mathematica® Support
Author: Phil Gregory
Publisher: Cambridge University Press
ISBN: 113944428X
Category: Mathematics
Page: N.A
View: 4819
Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at

Sport and Exercise Psychology

Author: Joanne Thatcher,Melissa Day,Rachel Rahman
Publisher: Learning Matters
ISBN: 1844458415
Category: Sports & Recreation
Page: 240
View: 7481
Electronic Inspection Copy available for instructors here This is a comprehensive and accessible text on exercise and sport psychology for students on sport science/sport and exercise science degrees. It adopts an integrated, thematic approach and covers all the required theory, concepts and research, accompanied by case studies to illustrate the applied nature of the material being covered. The book is split into two major sections, covering exercise psychology and sport psychology, and each chapter supports students as they progress from clear introductory material to more advanced discussions.

Machine Learning

A Practical Approach on the Statistical Learning Theory
Author: Rodrigo Fernandes de Mello,Moacir Antonelli Ponti
Publisher: Springer
ISBN: 3319949896
Category: Computers
Page: 362
View: 3301
This book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible. It starts with an introduction to Machine Learning concepts and algorithms such as the Perceptron, Multilayer Perceptron and the Distance-Weighted Nearest Neighbors with examples, in order to provide the necessary foundation so the reader is able to understand the Bias-Variance Dilemma, which is the central point of the Statistical Learning Theory. Afterwards, we introduce all assumptions and formalize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to study data spaces and improve classification results.

Statistics for Health Care Research

A Practical Workbook
Author: Susan K. Grove
Publisher: W B Saunders Company
ISBN: 9781416002260
Category: Medical
Page: 351
View: 773
nalysis techniques.

Machine Learning

a Concise Introduction
Author: Steven W. Knox
Publisher: John Wiley & Sons
ISBN: 1119439078
Category: Computers
Page: 352
View: 8146
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field—presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection— essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning: a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.

Understanding and Using Statistics in Psychology

A Practical Introduction
Author: Jeremy Miles,Philip Banyard
Publisher: SAGE
ISBN: 9780761943976
Category: Psychology
Page: 356
View: 4716
Understanding and Using Statistics in Psychology takes the fear out of psychological statistics to help students understand why statistics are carried out, how to choose the best test, how to carry out the tests, and then perform the analysis in SPSS. Emphasizing the place of statistical analysis in the process of conducting research, from design to report writing, this accessible and straightforward guide takes a non-technical approach, encouraging the reader to understand why a particular test is being used and what the results mean in the context of a psychological study. The focus is on meaning and understanding rather than numerical calculation.

The Research Process in Sport, Exercise and Health

Case Studies of Active Researchers
Author: Rich Neil,Sheldon Hanton,Scott Fleming,Kylie Wilson
Publisher: Routledge
ISBN: 1136455787
Category: Sports & Recreation
Page: 280
View: 5831
What are the challenges and potential pitfalls of real research? What decision-making process is followed by successful researchers? The Research Process in Sport, Exercise and Health fills an important gap in the research methods literature. Conventional research methods textbooks focus on theory and descriptions of hypothetical techniques, while the peer-reviewed research literature is mainly concerned with discussion of data and the significance of results. In this book, a team of successful researchers from across the full range of sub-disciplines in sport, exercise and health discuss real pieces of research, describing the processes they went through, the decisions that they made, the problems they encountered and the things they would have done differently. As a result, the book goes further than any other in bringing the research process to life, helping students identify potential issues and problems with their own research right at the beginning of the process. The book covers the whole span of the research process, including: identifying the research problem justifying the research question choosing an appropriate method data collection and analysis identifying a study’s contribution to knowledge and/or applied practice disseminating results. Featuring real-world studies from sport psychology, biomechanics, sports coaching, ethics in sport, sports marketing, health studies, sport sociology, performance analysis, and strength and conditioning, the book is an essential companion for research methods courses or dissertations on any sport or exercise degree programme.

Notational Analysis of Sport

Systems for Better Coaching and Performance in Sport
Author: Mike Hughes,Ian M. Franks
Publisher: Psychology Press
ISBN: 9780415290043
Category: Education
Page: 304
View: 3263
First published in 1997. Routledge is an imprint of Taylor & Francis, an informa company.

Probability and Statistics for Computer Science

Author: David Forsyth
Publisher: Springer
ISBN: 3319644106
Category: Computers
Page: 367
View: 1883
This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features: • A treatment of random variables and expectations dealing primarily with the discrete case. • A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. • A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. • A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. • A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. • A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. • A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.

Statistics for Linguistics with R

A Practical Introduction
Author: Stefan Th. Gries
Publisher: Walter de Gruyter
ISBN: 3110307472
Category: Language Arts & Disciplines
Page: 372
View: 6251
This book is the revised and extended second edition of Statistics for Linguistics with R. The volume is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. Just like the first edition, it is aimed at students, faculty, and researchers with little or no statistical background in statistics or the open source programming language R. It avoids mathematical jargon and discusses the logic and structure of quantitative studies and introduces descriptive statistics as well as a range of monofactorial statistical tests for frequencies, distributions, means, dispersions, and correlations. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, a revision of overview sections on statistical tests and regression modeling, a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA, and a new visual tool to identify the right statistical test for a given problem and data set. The amount of code available from the companion website has doubled in size, providing much supplementary material on statistical tests and advanced plotting.