Lecturers teaching big mixed cohort intro statistics courses cite one of the more frequent challenges their students encounter involves choices over which statistical test to use. Students, even if they have a basic grasp of statistics and which types of tests are out there, often make the wrong choice, or have difficulty in distinguishing between the types of tests for different types of data. This Little Quick Fix provides step-by-step support in narrowing down possible tests they could use so they know which test fits their data and variables, and which test will actually help them answer the questions they want to answer and create maximum impact from their data. Little Quick Fix titles provide quick but authoritative answers to the problems, hurdles, and assessment points students face in the research course, project proposal, or design—whatever their methods learning is. Lively, ultra-modern design; full-colour, each page a tailored design. An hour′s read. Easy to dip in and out of with clear navigation enables the reader to find what she needs—quick. Direct written style gets to the point with clear language. Nothing needs to be read twice. No fluff. Learning is reinforced through a 2-minute overview summary; 3-second summaries with super-quick Q&A DIY tasks create a work plan to accomplish a task, do a self-check quiz, solve a problem, get students to what they need to show their supervisor. Checkpoints in each section make sure students are nailing it as they go and support self-directed learning. How do I know I’m done? Each Little Quick Fix wraps up with a final checklist that allows the reader to self-assess they’ve got what they need to progress, submit, or ace the test or task.

Expanded and updated, the Third Edition of Gopal Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. The Third Edition now includes: - a new introduction to statistical testing with information to guide even the non-statistician through the book quickly and easily - real-world explanations of how and when to use each test with examples drawn from wide range of disciplines - a useful Classification of Tests table - all the relevant statistical tables for checking critical valu.

Zina O′Leary′s Research Question Little Quick Fix teaches students how to find their interest, hone it to a topic, and turn it into a research question that is relevant, interesting, and researchable. Little Quick Fix titles provide quick but authoritative answers to the problems, hurdles, and assessment points students face in the research course, project proposal or design—whatever their methods learning is. Lively, ultra-modern design; full-colour, each page a tailored design. An hour′s read. Easy to dip in and out of with clear navigation enables the reader to find what she needs—quick. Direct written style gets to the point with clear language. Nothing needs to be read twice. No fluff. Learning is reinforced through a 2-minute overview summary; 3-second summaries with super-quick Q&A DIY tasks create a work plan to accomplish a task, do a self-check quiz, solve a problem, get students to what they need to show their supervisor. Checkpoints in each section make sure students are nailing it as they go and support self-directed learning. How do I know I’m done? Each Little Quick Fix wraps up with a finale checklist that allows the reader to self-assess they’ve got what they need to progress, submit, or ace the test or task.

The second edition of this text is an introduction to the use of statistical tests in psychology experiments: statistics without panic. Presented in a new textbook format, its key objective is to enable students to select appropriate statistical tests to evaluate the significance of data obtained from psychological experiments. Improvements ion the organization of chapters emphasize even more clearly the principle of introducing complex experimental designs on a need to know basis, leaving more space for an extended interpretation of analysis of variance. In an important development for the second edition, students are introduced to modern statistical packages as a useful tool for calculations, the emphasis being on understanding and interpretation.

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.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

Choosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work. Features new to this edition: Now features information on using the popular free program, R Uses a simple key and flow chart to help you choose the right statistical test Aimed at students using statistics for projects and in practical classes Includes an extensive glossary and key to symbols to explain any statistical jargon No previous knowledge of statistics is assumed

"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

Probability theory

Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theoryfor the Behavioral Sciences provides both a broad overview and a