Statistics For People Who Think They Hate Statistics

Now in its third edition, this title teaches an often intimidating and difficult subject in a way that is informative, personable, and clear.

Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel 2016, Fourth Edition presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students will appreciate the book's unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including coverage of how to use functions and formulas, this edition also shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. The book walks readers through various statistical procedures, beginning with simple descriptive statistics, correlations, and graphical representations of data, and ending with inferential techniques, analysis of variance, and a new introductory chapter on working with large datasets and data mining using Excel.

Based on Neil J. Salkind’s bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students uncomfortable with the analysis portion of their work will appreciate the book′s unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques and then walks them through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. New to the Fourth Edition: A new chapter 20 dealing with large data sets using Excel functions and pivot tables, and illustrating how certain databases and other categories of functions and formulas can help make the data in big data sets easier to work with and the results more understandable. New chapter-ending exercises are included and contain a variety of levels of application. Additional TechTalks have been added to help students master Excel 2016. A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world. Basic maths instruction and practice exercises for those who need to brush up on their math skills are included in the appendix.

Designed for users already familiar with basic computer operations, Neil J. Salkind's Excel Statistics: A Quick Guide shows readers how to utilize the features of Microsoft® Excel to answer both simple and complex questions about data analysis. Part I explores thirty Excel functions, each one detailed on a two-page spread. The description and use of each function appear on one page with corresponding screen shots of the function in action on the facing page, allowing the user to see what the function looks like as it is being applied. Part II of the text contains fifteen Analysis Toolpak tools, each explained using the same two-page spread design as for the functions. Excel novices and experts alike will find this text not only practical but easy to use and engaging. Key Features: - Each function and tool is accompanied by an Excel file, accessible through the SAGE Web site, to be used as an example of each analysis. Access these files through the SAGE website (www.sagepub.com/salkindexcelstats) or through www.onlinefilefolder.com. - The screenshots and steps feature Microsoft Excel 2010 and are compatible with Microsoft 97-2003 and Excel 5.0/95. - Designed to be used as both an introduction and a reference book as needed. Perfect as an accompaniment to existing introductory statistics books or in a lab setting.

In an increasingly data-driven world, it is more important than ever for students as well as professionals to better understand basic statistical concepts. 100 Questions (and Answers) About Statistics addresses the essential questions that students ask about statistics in a concise and accessible way. It is perfect for instructors, students, and practitioners as a supplement to more comprehensive materials, or as a desk reference with quick answers to the most frequently asked questions.

"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

Statistics for Health Care Professionals is an accessible guide to understanding statistics within health care practice. Focusing on quantitative approaches to investigating problems, the book introduces the basic rules and principles of statistics. Challenging the notion that statistics are often incomprehensible and complex to use, the authors begin by presenting a `how to' section explaining how specific statistical tests can be performed. They also help readers to understand the language of statistics, which is often a stumbling block for those coming to the subject for the first time. The reader is taught how to calculate statistics by hand as well as being introduced to computer packages to make life easier, and then how to analyse these results. As the results of health care research are so integral to decision-making and developing new practice within the profession, the book encourages the reader to think critically about data analysis and research design, and how these can impact upon evidence based practice. This critical stance is also crucial in the assessment of the many reports and documents issued within the health industry. Statistics for Health Care Professionals includes practical examples of statistical techniques throughout, and the exercises within and at the end of each chapter help readers to learn and to develop proficiency. There is also a glossary at the end of the book for quick and easy referencing. This book is essential reading for those coming to statistics for the first time within a health care setting.