Get Your Data From Experiments

Offering guidance on doing experiments, this Little Quick Fix helps you select the most appropriate experiment for your research, collect and record data, minimise error, and ensure your experiment is ethical and reproducible.

"What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. Useful features for teaching or self-study: *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. Subject Areas/Keywords: analyses, coding, combined methods, data analysis, data collection, dissertation, graphical, interpretation, mixed methods, qualitative, quantitative, research analysis, research designs, research methods, social sciences, thesis, visual Audience: Researchers, instructors, and graduate students in a range of disciplines, including psychology, education, social work, sociology, health, and management; administrators and managers who need to make data-driven decisions"--

Data Literacy: How to Make Your Experiments Robust and Reproducible provides an overview of basic concepts and skills in handling data, which are common to diverse areas of science. Readers will get a good grasp of the steps involved in carrying out a scientific study and will understand some of the factors that make a study robust and reproducible.The book covers several major modules such as experimental design, data cleansing and preparation, statistical analysis, data management, and reporting. No specialized knowledge of statistics or computer programming is needed to fully understand the concepts presented. This book is a valuable source for biomedical and health sciences graduate students and researchers, in general, who are interested in handling data to make their research reproducible and more efficient. Presents the content in an informal tone and with many examples taken from the daily routine at laboratories Can be used for self-studying or as an optional book for more technical courses Brings an interdisciplinary approach which may be applied across different areas of sciences

How tech companies like Google, Airbnb, StubHub, and Facebook learn from experiments in our data-driven world—an excellent primer on experimental and behavioral economics Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of different online experiences. Once an esoteric tool for academic research, the randomized controlled trial has gone mainstream. No tech company worth its salt (or its share price) would dare make major changes to its platform without first running experiments to understand how they would influence user behavior. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world. Luca and Bazerman describe the central role experiments play in the tech sector, drawing lessons and best practices from the experiences of such companies as StubHub, Alibaba, and Uber. Successful experiments can save companies money—eBay, for example, discovered how to cut $50 million from its yearly advertising budget—or bring to light something previously ignored, as when Airbnb was forced to confront rampant discrimination by its hosts. Moving beyond tech, Luca and Bazerman consider experimenting for the social good—different ways that governments are using experiments to influence or “nudge” behavior ranging from voter apathy to school absenteeism. Experiments, they argue, are part of any leader's toolkit. With this book, readers can become part of “the experimental revolution.”

How to Design and Report Experiments is the perfect textbook and guide to the often bewildering world of experimental design and statistics. It provides a complete map of the entire process beginning with how to get ideas about research, how to refine your research question and the actual design of the experiment, leading on to statistical procedure and assistance with writing up of results. While many books look at the fundamentals of doing successful experiments and include good coverage of statistical techniques, this book very importantly considers the process in chronological order with specific attention given to effective design in the context of likely methods needed and expected results. Without full assessment of these aspects, the experience and results may not end up being as positive as one might have hoped. Ample coverage is then also provided of statistical data analysis, a hazardous journey in itself, and the reporting of findings, with numerous examples and helpful tips of common downfalls throughout. Combining light humour, empathy with solid practical guidance to ensure a positive experience overall, Designing and Reporting Experiments will be essential reading for students in psychology and those in cognate disciplines with an experimental focus or content in research methods courses.

Going green is a hot topic...and a hot science fair project. Author and scientist Elizabeth Snoke Harris knows what impresses, and she provides plenty of winning ideas, along with step-by-step guidance to insure that the end result is a success. Show how to harness energy with windmills, make a biogas generator, and create alternative fuels. Demonstrate green power with recycled paper, solar building, and compact fluorescent light bulbs. Test the ozone, be a "garbage detective,” and discuss how to reverse global warming. The importance of what children learn will go even beyond the science fair: they’ll have the knowledge to understand what’s happening to Planet Earth...and the desire to do something eco-friendly every day.

The straightforward, time-tested General Chemistry Laboratory Experiments is appropriate for two-semester general chemistry courses at the college level. Our Chemistry Laboratory Series is designed to actively engage your students in the process of learning how to be curious, precise, and safe in the laboratory. Our manuals are clearly written, engagingly illustrated, and affordably priced to make sure that your students’ first experiences in the laboratory provide a solid foundation for their future studies.

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books. Numerous pedagogical features further facilitate understanding: examples of published research demonstrate the applicability of each chapter’s content; flowcharts assist in choosing the most appropriate procedure; end-of-chapter lists of important formulas highlight key ideas and assist readers in locating the initial presentation of equations; useful programming code and tips are provided throughout the book and in associated resources available online, and extensive sets of exercises help develop a deeper understanding of the subject. Detailed solutions for some of the exercises and realistic data sets are included on the website (DesigningExperiments.com). The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. The book and its companion website with web apps, tutorials, and detailed code are ideal for students and researchers seeking the optimal way to design their studies and analyze the resulting data.

Until recently, most psychological research was conducted using subject samples in close proximity to the investigators--namely university undergraduates. In recent years, however, it has become possible to test people from all over the world by placing experiments on the internet. The number of people using the internet for this purpose is likely to become the main venue for subject pools in coming years. As such, learning about experiments on the internet will be of vital interest to all research psychologists. Psychological Experiments on the Internet is divided into three sections. Section I discusses the history of web experimentation, as well as the advantages, disadvantages, and validity of web-based psychological research. Section II discusses examples of web-based experiments on individual differences and cross-cultural studies. Section III provides readers with the necessary information and techniques for utilizing the internet in their own research designs. Innovative topic that will capture the imagination of many readers Includes examples of actual web based experiments

A student guide to neuroscience research including how to select a topic, analyze data, and present research.

This book will provide scientists with a better understanding of statistics, improving their decision-making and reducing animal use.

Experience the magic of biology in your own home lab. This hands-on introduction includes more than 30 educational (and fun) experiments that help you explore this fascinating field on your own. Perfect for middle- and high-school students and DIY enthusiasts, this full-color guide teaches you the basics of biology lab work and shows you how to set up a safe lab at home. The Illustrated Guide to Home Biology Experiments is also written with the needs of homeschoolers firmly in mind, as well as adults who are eager to explore the science of nature as a life-long hobby. To get the most from the experiments, we recommend using this guide in conjunction with a standard biology text, such as the freely downloadable CK-12 Biology (ck-12.org). Master the use of the microscope, including sectioning and staining Build and observe microcosms, soda-bottle worlds of pond life Investigate the chemistry of life from simple acids, bases, and buffers to complex carbohydrates, proteins, lipids, enzymes, and DNA Extract, isolate, and observe DNA Explore photosynthesis, osmosis, nitrogen fixation, and other life processes Investigate the cell cycle (mitosis and cytokinesis) Observe populations and ecosystems, and perform air and water pollution tests Investigate genetics and inheritance Do hands-on microbiology, from simple culturing to micro-evolution of bacteria by forced selection Gain hands-on lab experience to prepare for the AP Biology exam Through their company, The Home Scientist, LLC (thehomescientist.com/biology), the authors also offer inexpensive custom kits that provide specialized equipment and supplies you’ll need to complete the experiments. Add a microscope and some common household items and you’re good to go.

The third edition of this text offers expanded advice and updated guidelines to students on designing and writing reports of experimental and other studies in psychology.

On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data. This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow. Understand the relationship between data, business, and design Get a firm grounding in data, data types, and components of A/B testing Use an experimentation framework to define opportunities, formulate hypotheses, and test different options Create hypotheses that connect to key metrics and business goals Design proposed solutions for hypotheses that are most promising Interpret the results of an A/B test and determine your next move

Every year, six million students enter college with the intention of becoming a science major by the time they graduate, only 60% of them will actually follow through. This means that close to 2.4 million students, every year, drop out of the science track. According to the New York Times, roughly 40% of students planning science majors either end up switching their major or fail to get any degree. Furthermore, aspiring pre-medical students (who comprise a large percentage of the freshmen class at most colleges, but who may not be science majors) often cite frustrations with science coursework/grading as a main motivation for changing their career plans. What Every College Science Student Should Know teaches students everything they need to know about how to succeed in school and after graduation. It s a portable guide and mentor that teaches study skills, course selection and mastery, how to do scientific research, what to expect from majors, how to find mentors, and how to apply learned skills to career development and enjoyment. Written by recent college graduates for entering college students and seniors in high school, What Every College Science Student Should Know is an invaluable resource for those who want to pursue a science degree, and it s also an inspiring narrative of remarkable students who are already changing the world through science."

PsychoPy is an open-source software package for creating rich, dynamic experiments in psychology, neuroscience and linguistics. Written by its creator, this book walks you through the steps of building experiments in PsychoPy, from using images to discovering lesser-known features, and from analysing data to debugging your experiment. Divided into three parts and with unique extension exercises to guide you at whatever level you are at, this textbook is the perfect tool for teaching practical undergraduate classes on research methods, as well as acting as a comprehensive reference text for the professional scientist. Essential reading for anyone using PsychoPy software, the second edition has been fully updated and includes multiple new chapters about features included in recent versions of PsychoPy, including running studies online and collecting survey data. Part I teaches you all the basic skills you need (and some more advanced tips along the way) to design experiments in behavioral sciences. Each chapter introduces anew concept but will offer a series of working experiments that you can build on. Part II presents more details important for professional scientists intending to use PsychoPy for published research. This part is recommended reading for science professionals in any discipline. Part III covers a range of specialist topics, such as those doing fMRI research, or those studying visual perception. "This book fills an incredibly important gap in the field. Many users of PsychoPy will be excited to learn that there is now a highly accessible and well-designed written guide to refine their skills." – Susanne Quadflieg, University of Bristol

This book will help undergraduate psychology students to write practical reports of experimental and other quantitative studies in psychology. It is designed to help with every stage of report writing and provides a resource that students can refer to throughout their degree, up-to and including when writing up a final year undergraduate project. Now fully updated in its fourth edition, this book maps to the seventh edition of the APA guidelines and offers more comprehensive advice, guidelines and recommendations than ever before. Students will benefit from: •Coverage of different forms of quantitative study, including online studies and studies that use questionnaires, as well as experiments •A range of handy test yourself questions (with answers at the end of the book) •Self-reflection questions to prompt deeper understanding •Summary sections that articulate the main points and provide a useful revision aid •An Index of Concepts indicating where in the book every concept is introduced and defined •Updated advice on how to find and cite references •Expanded coverage of ethics in quantitative research, including how to write ethically •Common mistake symbols, flagging areas where its easy to be caught out Peter Harris is Emeritus Professor of Psychology at the University of Sussex, UK where he led the Social and Applied Psychology Group. He has taught research design and statistics for many years. He has published extensively in social and health psychology. Matthew J. Easterbrook is Senior Lecturer in Psychology at the University of Sussex, UK. He has taught statistics at a national and international level. Jessica S. Horst is Reader in Psychology at the University of Sussex, UK, where she is also the Director of Teaching and Learning. She has taught research methods in both the USA and the UK.

Based on a series of experiments that have been tried and tested over a period of several years at Universities in the United Kingdom, this is a book aimed at undergraduate physics students.