Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (https://stanlazic.github.io/EDLB.html) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.

The effective design of scientific experiments is critical to success, yet graduate students receive very little formal training in how to do it. Based on a well-received course taught by the author, Experimental Design for Biologistsfills this gap. Experimental Design for Biologistsexplains how to establish the framework for an experimental project, how to set up a system, design experiments within that system, and how to determine and use the correct set of controls. Separate chapters are devoted to negative controls, positive controls, and other categories of controls that are perhaps less recognized, such as “assumption controls†and “experimentalist controls†. Furthermore, there are sections on establishing the experimental system, which include performing critical “system controls†. Should all experimental plans be hypothesis-driven? Is a question/answer approach more appropriate? What was the hypothesis behind the Human Genome Project? What color is the sky? How does one get to Carnegie Hall? The answers to these kinds of questions can be found in Experimental Design for Biologists. Written in an engaging manner, the book provides compelling lessons in framing an experimental question, establishing a validated system to answer the question, and deriving verifiable models from experimental data. Experimental Design for Biologistsis an essential source of theory and practical guidance in designing a research plan.

A guide to designing lab-based biological experiments that have low bias, high precision and widely applicable results.

Regression, analysis of variance, correlation, graphical.

Most research in the life sciences involves a core set of molecular-based equipment and methods, for which there is no shortage of step-by-step protocols. Nonetheless, there remains an exceedingly high number of inquiries placed to commercial technical support groups, especially regarding problems. Molecular Biology Problem Solver: A Laboratory Guide asks the reader to consider crucial questions, such as: Have you selected the most appropriate research strategy? Have you identified the issues critical to your successful application of a technique? Are you familiar with the limitations of a given technique? When should common procedural rules of thumb not be applied? What strategies could you apply to resolve a problem? A unique question-based format reviews common assumptions and laboratory practices, with the aim of offering a firm understanding of how techniques and procedures work, as well as how to avoid problems. Some major issues explored by the book's expert contributors include: Working safely with biological samples and radioactive materials DNA and RNA purification PCR Protein and nucleid acid hybridization Prokaryotic and eukaryotic expression systems Properly using and maintaining laboratory equipment

A good working knowledge of statistical principles is needed for both the design and analysis of biological experiments and the subsequent handling of the large amounts of data generated if worthwhile, reliable conclusions are to be reached. Practical Statistics for Experimental Biologists, Second Edition provides biologists with a user-friendly, non-technical introduction to the basics of statistics. The book has been thoroughly revised and updated to incorporate: * Worked examples and printouts from MINITAB * Relevant case studies and applications * Further Notes section for background explanations Written by a biologist with extensive experience of applying statistical procedures to experimental systems, this book will be invaluable to undergraduates, postgraduates and researchers in microbiology, immunology, biochemistry, botany, zoology, physiology, pharmacology and pharmacy. Review of the First Edition "...strongly recommended as the current first choice both for students and established research workers." Society for General Microbiology Quarterly "...the book is refreshingly free from jargon, is well illustrated and is to be recommended." Trends in Biochemical Sciences "It is written in an easy style, and can be thoroughly recommended..." Trends in Pharmacological Sciences

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.