All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises--with solutions—illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.
This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyze data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics. Specific examples are worked through step by step in the text. Emphasis is placed on the need to think about whether a calculated error is sensible. Students should take this book with them to the laboratory, and the format is intended to make this convenient. The book will provide the necessary understanding of what is involved, should inspire confidence in the method of estimating errors, and enable numerical calculations without too much effort.
In the investigation of human behaviour, statistical techniques are employed widely in the social sciences. Whilst introductory statistics courses cover essential techniques, the complexities of behaviour demand that more flexible and comprehensive methods are also employed. Analysis of Variance (ANOVA) has become one of the most common of these and it is therefore essential for both student and researcher to have a thorough understanding of it. A Student's Guide to Analysis of Variance covers a range of statistical techniques associated with ANOVA, including single and multiple factor designs, various follow-up procedures such as post-hoc tests, and how to make sense of interactions. Suggestions on the best use of techniques and advice on how to avoid the pitfalls are included, along with guidelines on the writing of formal reports. Introductory level topics such as standard deviation, standard error and t-tests are revised, making this book an invaluable aid to all students for whom ANOVA is a compulsory topic. It will also serve as a useful refresher for the more advanced student and practising researcher.
Collaboration Among Professionals, Students, Families, and Communities provides a foundation for understanding concepts of collaborative learning along with strategies for the application of collaborative skills in teaching. The book moves logically from issues of macro-collaboration (district and school) to micro-collaboration (individual student focus and co-teaching) in K-12 environments before concluding with strategies for family and community collaboration. Significant emphasis is placed on knowledge, skills, and teaching models for pre-service and in-service teachers in general education, special education, and of diverse students including English Learners. Each chapter includes meaningful pedagogical features such as: Learning objectives A case study illustrating the implementation of information presented A case study challenging the reader to apply the information learned in the chapter Study questions for readers in Comprehension Checks at key points in the chapter Highlights of major points in a chapter summary for aid in studying content University, school, and community-based application activities A companion website features additional resources, including PowerPoint presentations, practice tests, suggested video and Internet resources, and advanced application activities.
A refreshing, student-focused introduction to the use of statistics in the study of the biosciences. Emphasising why statistical techniques are essential tools for bioscientists, Biomeasurement removes the stigma attached to statistics by giving students the confidence to use key techniques for themselves.
Praise for Common Errors in Statistics (and How to AvoidThem) "A very engaging and valuable book for all who use statistics inany setting." —CHOICE "Addresses popular mistakes often made in data collection andprovides an indispensable guide to accurate statistical analysisand reporting. The authors' emphasis on careful practice, combinedwith a focus on the development of solutions, reveals the truevalue of statistics when applied correctly in any area ofresearch." —MAA Reviews Common Errors in Statistics (and How to Avoid Them), FourthEdition provides a mathematically rigorous, yet readilyaccessible foundation in statistics for experienced readers as wellas students learning to design and complete experiments, surveys,and clinical trials. Providing a consistent level of coherency throughout, the highlyreadable Fourth Edition focuses on debunking popular myths,analyzing common mistakes, and instructing readers on how to choosethe appropriate statistical technique to address their specifictask. The authors begin with an introduction to the main sources oferror and provide techniques for avoiding them. Subsequent chaptersoutline key methods and practices for accurate analysis, reporting,and model building. The Fourth Edition features newly addedtopics, including: Baseline data Detecting fraud Linear regression versus linear behavior Case control studies Minimum reporting requirements Non-random samples The book concludes with a glossary that outlines key terms, andan extensive bibliography with several hundred citations directingreaders to resources for further study. Presented in an easy-to-follow style, Common Errors inStatistics, Fourth Edition is an excellent book for studentsand professionals in industry, government, medicine, and the socialsciences.
A Resource for Designing and Implementing Intervention Programsfor At-Risk Learners This authoritative resource provides step-by-step procedures forplanning, selecting, and tailoring interventions for at-risklearners with a unique focus on how to individualize interventionsusing actual case examples. In addition, this volume offersguidelines for gathering and interpreting data in a manner thatassists in identifying targets for intervention and rich discussionand information relating to specific academic, cognitive, andbehavioral manifestations of students with learning difficulties inreading, math, writing, and oral language. Practitioners will alsorecognize and learn how to intervene with students from underservedand mis-served populations who are at risk for learning failureincluding English-language learners and students from impoverishedenvironments. Each chapter describes how specific difficulties interfere withclassroom tasks and explain how to select, modify, or otherwisetailor an intervention based on that information. As with allvolumes in the Essentials of Psychological Assessmentseries, this volume includes callout boxes highlighting keyconcepts, extensive illustrative material, and test questions. Thecompanion CD-ROM provides additional worksheets, case studies, andhandouts.