Designed to be hands-on with the user performing the analyses alongside on their computer as they read through each chapter. Yockey For courses in Statistics and Research Methods.
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The datasets used in Quantitative Data Analysis with SPSS 14, 15 & 16 are available online at: http: //in addition a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available here free of charge to lecturers who adopt the book. For the first time, the book includes a helpful glossary of key terms. Each chapter contains worked examples to illustrate the points raised and ends with a comprehensive range of exercises which allow the reader to test their understanding of the topic.
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No previous familiarity with computing or statistics is required to benefit from this step-by-step guide to statistical techniques, which includes: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis The authors discuss key issues facing the newcomer to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS. Quantitative Data Analysis with SPSS 14, 15 and 16 by Alan Bryman Duncan Cramer This edition has been completely updated to accommodate the needs of users of SPSS Releases 14, 15 and 16, whilst still being applicable to those using SPSS Releases 10-13. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics. 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. 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. Sections explain the conceptual machinery underlying the statistical tests. 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. 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 chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept.
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. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. Reise 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. A Conceptual Guide to Statistics Using SPSS by Elliot T.