This text guides the novice user through the process of entering and analyzing data using SPSS for Windows. It assumes no prior knowledge of computing, research methods or statistics, and covers the statistical techniques used in psychology.
This text guides the novice user through the process of entering and analyzing data using SPSS for Windows. It assumes no prior knowledge of computing, research methods or statistics, and covers the statistical techniques used in psychology.
Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements. The book looks at the process of empirical research into the following seven stages: Formulation of the problem Stipulation of the precision requirements Selecting the statistical model for the planning and analysis The (optimal) design of the experiment or survey Performing the experiment or the survey Statistical analysis of the observed results Interpretation of the results.
Written by an experienced teacher of statistics, the new edition of this accessible yet authoritative textbook covers all areas of undergraduate statistics and provides a firm foundation upon which students can build their own knowledge. Featuring new chapters on Bayesian and multiple regression analysis, this book gives students a working understanding of how to conduct reliable and methodical research using statistics. Brysbaert illustrates the key concepts using examples from psychological research, with clear formulas and explanations for calculations. With helpful chapter-by-chapter guidance for carrying out tests using SPSS, as well as coverage of jamovi and JASP software, this book aims to develop students' confidence in statistical analysis, and to take the fear out of the topic. It offers an easily navigable layout filled with features that help learners to avoid common pitfalls and check their understanding along the way. This engaging and informative guide is essential reading for undergraduate psychology students taking courses in research methods and statistics. New to this Edition: - Chapters on Bayesian analysis, mixed-effects models, and multiple regression analysis - Coverage of jamovi and JASP, two free statistical packages
The introduction to statistics that psychology students can't afford to be without Understanding statistics is a requirement for obtaining and making the most of a degree in psychology, a fact of life that often takes first year psychology students by surprise. Filled with jargon-free explanations and real-life examples, Psychology Statistics For Dummies makes the often-confusing world of statistics a lot less baffling, and provides you with the step-by-step instructions necessary for carrying out data analysis. Psychology Statistics For Dummies: Serves as an easily accessible supplement to doorstop-sized psychology textbooks Provides psychology students with psychology-specific statistics instruction Includes clear explanations and instruction on performing statistical analysis Teaches students how to analyze their data with SPSS, the most widely used statistical packages among students
"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
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.
This sixth edition of Research Methods and Statistics in Psychology has been fully revised and updated, providing students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project giving advice on planning and conducting studies, analysing data and writing up reports. The book provides clear coverage of statistical procedures, and includes everything needed from nominal level tests to multi-factorial ANOVA designs, multiple regression and log linear analysis. It features detailed and illustrated SPSS instructions for all these procedures eliminating the need for an extra SPSS textbook. New features in the sixth edition include: "Tricky bits" - in-depth notes on the things that students typically have problems with, including common misunderstandings and likely mistakes. Improved coverage of qualitative methods and analysis, plus updates to Grounded Theory, Interpretive Phenomenological Analysis and Discourse Analysis. A full and recently published journal article using Thematic Analysis, illustrating how articles appear in print. Discussion of contemporary issues and debates, including recent coverage of journals’ reluctance to publish replication of studies. Fully updated online links, offering even more information and useful resources, especially for statistics. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. A companion website (www.routledge.com/cw/coolican) provides additional exercises, revision flash cards, links to further reading and data for use with SPSS.
'Statistics Without Maths for Psychology' provides an accessible description of key statistical concepts and techniques needed by psychology students, avoiding as much maths as possible.