Practical Statistics for Educators


Book Description

Practical Statistic for Educators, 6th Edition is a clear and easy-to-follow book written specifically for education students in introductory statistics and action research courses. It is also an invaluable resource and guidebook for educational practitioners who wish to study their own settings and for those involved in program evaluation. The focus of the book is on essential concepts in educational statistics, understanding when to use various statistical tests, and how to interpret results. This book introduces educational students and practitioners to the use of statistics in education and basic concepts in statistics are explained in clear language. All of the examples used to explain the use of statistics in educational research are taken from the field of education and serve to illustrate the various concepts, terms, statistical tests, and data interpretations that are discussed in the book. Formulas and equations are used sparingly and readers are not required to do any computations. The book also includes a discussion of testing, test score interpretation, reliability, and validity. A chapter on survey design and analysis provide the book readers with examples which demonstrate how the different statistical tests introduced in the book can be used to analyzed survey data. Chapter previews are provided, as well as succinct end-of-chapter summaries. The book’s glossary of main terms and concepts helps readers navigate the book and easily find useful information. Review exercises are included at the end of the book to allow readers to practice and apply their newly-acquired knowledge and skills.




Practical Statistics for Data Scientists


Book Description

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data




Practical Statistics


Book Description

Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.




Practical Statistics for Students


Book Description

This bestselling textbook is designed to help students understand parametric and nonparametric statistical methods so that they can tackle research problems successfully. By working through this book carefully and systematically, those who may not have a strong background in mathematics will gain a thorough grasp of the most widely used statistical methods in the social sciences.




Practical Statistics for Environmental and Biological Scientists


Book Description

All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to understand. Practical Statistics for Environmental and Biological Scientists provides a concise, user-friendly, non-technical introduction to statistics. The book covers planning and designing an experiment, how to analyse and present data, and the limitations and assumptions of each statistical method. The text does not refer to a specific computer package but descriptions of how to carry out the tests and interpret the results are based on the approaches used by most of the commonly used packages, e.g. Excel, MINITAB and SPSS. Formulae are kept to a minimum and relevant examples are included throughout the text.




Practical Statistics for Medical Research


Book Description

Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.




Practical Statistics for Field Biology


Book Description

Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings. An understanding of statistical principles and methods is essential for any scientist but is particularly important for those in the life sciences. The field biologist faces very particular problems and challenges with statistics as "real-life" situations such as collecting insects with a sweep net or counting seagulls on a cliff face can hardly be expected to be as reliable or controllable as a laboratory-based experiment. Acknowledging the peculiarites of field-based data and its interpretation, this book provides a superb introduction to statistical analysis helping students relate to their particular and often diverse data with confidence and ease. To enhance the usefulness of this book, the new edition incorporates the more advanced method of multivariate analysis, introducing the nature of multivariate problems and describing the the techniques of principal components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included. It will be extremely useful to undergraduates studying ecology, biology, and earth and environmental sciences and of interest to postgraduates who are not familiar with the application of multiavirate techniques and practising field biologists working in these areas.




Quantifying the User Experience


Book Description

Quantifying the User Experience: Practical Statistics for User Research, Second Edition, provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website? This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. - Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practices - Includes new and revised information on standardized usability questionnaires - Includes a completely new chapter introducing correlation, regression, and analysis of variance - Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing data - Recommends ways for researchers and practitioners to communicate results to stakeholders in plain English




International Handbook of Research in Statistics Education


Book Description

This handbook connects the practice of statistics to the teaching and learning of the subject with contributions from experts in several disciplines. Chapters present current challenges and methods of statistics education in the changing world for statistics and mathematics educators. Issues addressed include current and future challenges in professional development of teachers, use of technology tools, design of learning environments and appropriate student assessments. This handbook presents challenging and inspiring international research perspectives on the history and nature, current issues, and future directions of statistics education and statistics education research.




Measurement and Statistics for Teachers


Book Description

Measurement and Statistics for Teachers deftly combines descriptive statistics and measurement in the classroom into a student-friendly, practical volume. Based on a course taught by the author for the past 25 years, this book offers to undergraduate education students a clear account of the basic issues in measurement and details best practices for administering performance assessments, interpreting test scores, and evaluating student writing. This second edition includes updated pedagogical features, timely discussions of student assessment, state standards (including NCLB), and an expanded focus that incorporates the needs of Early Childhood, Elementary, and Secondary teachers.