"What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. Useful features for teaching or self-study: *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. Subject Areas/Keywords: analyses, coding, combined methods, data analysis, data collection, dissertation, graphical, interpretation, mixed methods, qualitative, quantitative, research analysis, research designs, research methods, social sciences, thesis, visual Audience: Researchers, instructors, and graduate students in a range of disciplines, including psychology, education, social work, sociology, health, and management; administrators and managers who need to make data-driven decisions"--

A thorough understanding of biology, no matter which subfield, requires a thorough understanding of statistics. As in previous editions, Havel and Hampton (with new co-author Scott Meiners) ground students in all essential methods of descriptive and inferential statistics, using examples from different biological sciences. The authors have retained the readable, accessible writing style popular with both students and instructors. Pedagogical improvements new to this edition include concept checks in all chapters to assist students in active learning and code samples showing how to solve many of the book's examples using R. Each chapter features numerous practice and homework exercises, with larger data sets available for download at waveland.com.

This popular hands-on text teaches students how to use Microsoft Excel to solve the kind of statistical problems that arise in business and elsewhere. Even students with no previous experience using computer spreadsheets will find that this text's step-by-step approach, extensive tutorials, and examples, make it easy to learn how to use Excel for analyzing data sets. A CD-ROM that accompanies the text contains StatPlus 2.0 data sets and exercises.

Explore, create, and manage highly interactive data visualizations using Microsoft Power BI Extract meaningful business insights from your disparate enterprise data using the detailed information contained in this practical guide. Written by a recognized BI expert and bestselling author, Data Analysis with Microsoft Power BI teaches you the skills you need to interact with, author, and maintain robust visualizations and custom data models. Hands-on exercises based on real-life business scenarios clearly demonstrate each technique. Publishing your results to the Power BI Service (PowerBI.com) and Power BI Report Server are also fully covered. Inside, you will discover how to: •Understand Business Intelligence and self-service analytics •Explore the tools and features of Microsoft Power BI •Create and format effective data visualizations •Incorporate advanced interactivity and custom graphics •Build and populate accurate data models •Transform data using the Power BI Query Editor •Work with measures, calculated columns, and tabular models •Write powerful DAX language scripts •Share content on the PowerBI Service (PowerBI.com) •Store your visualizations on the Power BI Report Server

Quantifying Behavior the JWatcher Way provides detailed instructions for the freely distributed computer program JWatcher. This Macintosh/Windows application can be used to address any theoretical problem that requires a complex sequence of actions to be scored by a human observer. More than simply a computer manual, this text provides laboratory exercises and strategic advice to help both students and professionals learn how to quantify and analyse behaviour.

"There are fifteen major breakthroughs in technical analysis! SEVEN of these breakthroughs are new, never-before-revealed material!" - George Lane, Stochastics Originator. As professional traders approach the 21st century, accelerating technological change threatens to make conventional technical studies and indicators ineffective. To compete in this changing environment, these professionals need radical new uses and combinations of indicators and formulas to keep their competitive edge. Not a primer for the novice, TECHNICAL ANALYSIS FOR THE TRADING PROFESSIONAL resets the scales, arming today's professional trader with new, unique, and never-before-seen formulas and uses of key market indicators and techniques.

B>KEY BENEFIT: " After reading this book, a user with limited statistical experience should have a stronger ability to understand the description they provide of the variable or relationship being described. This guide to the statistical procedures in SPSS Base 8.0 contains several examples for each procedure, starting with default operations and moving on through the most commonly used optional specifications. It discusses the assumptions required by each procedure, checking the data for these assumptions, and finding strategies to deal with data that do not meet required assumptions. The bulk of this guide focuses on output, on understanding what the statistics mean and how the different statistics relate to each other. The book is designed to be used with the SPSS Base 8.0 User's Guide.

This is a guide to the statistical procedures in SPSS Base 7.5, containing several examples for each procedure, starting with default operations and proceeding to the most commonly-used optional specifications. This text also discusses the assumptions required by each procedure, checking the data for those assumptions, and finding strategies to deal with data which does not meet required assumptions.