Practical Statistics For Students

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.

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

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 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 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.

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.

The fourth edition of the Study Guide for Practical Statistics for Educators serves as a user-friendly and accessible way for students to better understand the concepts introduced in its companion textbook, Practical Statistics for Educators. With clear and straightforward exercises, the workbook allows students to reinforce their knowledge of statistics. Most importantly, students are given the answers and an explanation for why the correct answer is the better than the other choices. New in this edition are accompanying Excel exercises.

Practical Statistics is for anyone who wants to learn basic statistics for work, school, research, or the sheer enjoyment of gaining new knowledge. If you are practical, decision-oriented person, then Practical Statistics is what you need to facilitate your introduction to the fascinating and powerful tools of statistical analysis.