The Process Of Statistical Analysis In Psychology

The Process of Research and Statistical Analysis in Psychology presents integrated coverage of psychological research methods and statistical analysis to illustrate how these two crucial processes work together to uncover new information. Best-selling author Dawn M. McBride draws on over 20 years of experience using a practical step-by-step approach in her teaching to guide readers through the full process of designing, conducting, and presenting a research study. The text opens with introductory discussions of why psychologists conduct and analyze research before digging into the process of designing an experiment and performing statistical analyses. Each chapter concludes with exercises and activities that promote critical thinking, the smart consumption of research, and practical application. Readers will come away with a complete picture of the role that research plays in psychology as well as their everyday lives.

This new introductory statistics text from Dawn M. McBride, best-selling author of The Process of Research in Psychology, covers the background and process of statistical analysis, along with how to use essential tools for working with data from the field. Research studies are included throughout from both the perspective of a student conducting their own research study and of someone encountering research in their daily life. McBride helps readers gain the knowledge they need to become better consumers of research and statistics used in everyday decision-making and connects the process of research design with the tools employed in statistical analysis. Instructors and students alike will appreciate the extra opportunities for practice with the accompanying Lab Manual for Statistical Analysis, also written by McBride and her frequent collaborator, J. Cooper Cutting.

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.

Basic statistical concepts such as probability, estimation and inference, and their role in research design and analysis are presented in this volume. The author demonstrates which statistical test to use in given circumstances and how to use it, drawing on data from psychology and education.; Written for those without a strong mathematical background, the book's examples can be worked using a pocket calculator. "Real life" data are analyzed using statistical software (SAS), output is interpreted, and a decision chart is presented which summarizes considerations when choosing a statistical test.

Taking a non-technical approach, 'Understanding and Using Statistics in Psychology' encourages the reader to understand why a particular test is being used and what the results mean in the context of a psychological study, focusing on meaning and understanding rather than mindless numerical calculations.

Focusing on the needs and teaching methods for both students and lecturers, this represents a complete package for teaching statistics to psychology undergraduates.

STATISTICAL METHODS FOR PSYCHOLOGY, 8E, International Edition surveys the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasizes conceptual understanding. This Eighth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. New and expanded topics—reflecting the evolving realm of statistical methods—include effect size, meta-analysis, and treatment of missing data.

Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.