An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

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Experimental Design and Data Analysis for Biologists

A correlational study examined relationships between motivational orientation, self-regulated learning, and classroom academic performance for 173 seventh graders from eight science and seven English classes. A self-report measure of student self-efficacy, intrinsic value, test anxiety, self-regulation, and use of learning strategies was administered, and performance data were obtained from work on classroom assignments. Self-efficacy and intrinsic value were positively related to cognitive engagement and performance. Regression analyses revealed that, depending on the outcome measure, self-regulation, self-efficacy, and test anxiety emerged as the best predictors of performance. Intrinsic value did not have a direct influence on performance but was strongly related to self-regulation and cognitive strategy use, regardless of prior achievement level. The implications of individual differences in motivational orientation for cognitive engagement and self-regulation in the classroom are discussed. Self-regulation of cognition and behavior is an important aspect of student learning and academic performance in the classroom context (Corno & Mandinach, 1983; Corno & Rohrkemper, 1985). There are a variety of definitions of selfregulated learning, but three components seem especially important for classroom performance. First, self-regulated learning includes students' metacognitive strategies for planning, monitoring, and modifying their cognition (e.g., Brown, Bransford, Campione, & Ferrara, 1983; Corno, 1986; Zim

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Motivational and self-regulated learning components of classroom academic performance.

Praise for previous editions: 'This book really is a life saver! If the mere thought of statistics gives you a headache, then this is the book for you' - Statistics student, UK. 'I just wanted to say how much I value Julie Pallant's "SPSS Survival Manual". It's quite the best text in SPSS I've encountered and I recommend it to anyone who's listening!' -- Professor Carolyn Hicks, Birmingham University, UK. 'one of the most useful functional pieces of instruction I have seen. So, gold star and thanks' - Instructional designer, USA. 'There are several SPSS manuals published and this one really does 'do what it says on the tin' ...Whether you are a beginner doing your BSc or struggling with your PhD research (or beyond!), I wholeheartedly recommend this book' - "British Journal of Occupational Therapy", UK.Praise for the new edition: 'An excellent introduction to using SPSS for data analysis ...It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided' - Associate Professor George Dunbar, Department of Psychology, University of Warwick, UK. In this fully revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques.She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting SPSS output and an example of how to present the results in a report. For both beginners and experienced SPSS users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the "SPSS Survival Manual" is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. In this third edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output in version 15. A new flowchart is included for SPSS procedures, and factor analysis procedures have been streamlined. It also includes more examples and material on syntax. Additional data files are available on the book's supporting website.

SPSS survival manual : a step by step guide to data analysis using SPSS for Windows

We describe the development and validation of a new instrument, KEYS: Assessing the Climate for Creativity, designed to assess perceived stimulants and obstacles to creativity in organizational work environments. The KEYS scales have acceptable factor structures, internal consistencies, test-retest reliabilities, and preliminary convergent and discriminant validity. A construct validity study shows that perceived work environments, as assessed by the KEYS scales, discriminate between high-creativity projects and low-creativity projects; certain scales discriminate more strongly and consistently than others. We discuss the utility of this tool for research and practice.

Assessing the Work Environment for Creativity

Click on the arrow button to move the variable name into Chapter 4 Creating a data file and entering data 39 Step 2: Enter the data Spss survival. The SPSS Survival Manual throws a lifeline to students and researchers grappling with this data analysis software.In this thoroughly revised edition of her. Download PDF SPSS Survival Manual A step by step guide to data analysis using SPSS. SPSS SURVIVAL MANUAL. Are you come upon Spss Survival Manual? Great! We have the file you need: spss survival manual. The spss survival manual. To cite this article: Yeung, Polly. SPSS survival manual. A step by step guide to data analysis using IBM SPSS (5th ed) (Book Review) (online). Aotearoa New.

SPSS Survival Manual

This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.

J Stevens

Papers

Applied Multivariate Statistics for the Social Sciences