Spss Statistics A Practical Guide With Student Resource Access 12 Months
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SPSS Statistics: A Practical Guide with Student Resource Access 12 Months
SPSS is enormously powerful and challenging to learn. This popular handbook lets students get hands-on with the statistical procedures they need. Full colour screen shots, step-by-step guidance and examples with annotated outputs help students learn. For students of psychology, marketing and research in any discipline. An essential practical guide to using the latest version of IBM SPSS Statistics. New, print versions of this book come with bonus online study tools on the CourseMate Express platform Learn more about the online tools cengage.com.au/learning-solutions
SPSS Statistics: A Practical Guide 5e
SPSS Statistics: A Practical Guide gives students step-by-step guidance through the process of using SPSS software to analyse, interpret and report on data. This spiral bound text is concise yet detailed, and is praised for its friendly, practical, and visual pedagogical approach that focuses on ‘doing’. The illustrated step-by-step examples work through each statistical procedure and are followed by interpretation and reporting of results in APA style. Resources for the instructor include Instructor Manual, PowerPoints, practical exercises and datasets, revision quizzes, syntax sets, and more.
A Conceptual Guide to Statistics Using SPSS
This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures. Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics.