--- title: Experimental Design description: This discipline covers the planning and structuring of scientific experiments to ensure valid statistical analysis. Learners will understand how to define variables, control confounding factors, and select appropriate sampling methods to establish causal relationships. category: programming-tech subcategory: data-science difficulty: beginner, intermediate, advanced url: /subject/experimental-design --- # Experimental Design This discipline covers the planning and structuring of scientific experiments to ensure valid statistical analysis. Learners will understand how to define variables, control confounding factors, and select appropriate sampling methods to establish causal relationships. ## Available Resources 4 Books • 2 Courses • 6 Websites ## Websites ### 1. Seeing Theory An interactive, D3.js-based walkthrough of probability and statistics in six chapters, from basic probability and distributions through frequentist inference, Bayesian inference and regression analysis. Parameters are manipulable, so sampling behaviour and fit are visible directly. **Difficulty:** Beginner | **Price:** Free **Link:** https://seeing-theory.brown.edu/basic-probability/index.html **Tags:** probability, statistics, data-visualization, regression, bayesian-inference ### 2. NIST Engineering Statistics Handbook NIST's free reference chapter on designing experiments, covering completely randomized, randomized block, full and fractional factorial, and response surface designs, plus how to analyze, model, and interpret the resulting data. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.itl.nist.gov/div898/handbook/pri/section1/pri16.htm **Tags:** statistics, design-of-experiments, free-reference, doe ### 3. statisticshowto.com Statistics How To is a practical statistics learning site that explains core concepts with clear, step-by-step tutorials and worked examples. It covers hypothesis testing (including p-values and test types) along with a wide range of other stats topics and handy calculators. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://statisticshowto.com **Tags:** websites, mathematics-statistics, statistics-and-probability ### 4. stattrek.com StatTrek is an online statistics resource that provides clear tutorials and explanations of probability and statistics. It also features free calculators for distributions, hypothesis tests, confidence intervals, and other statistical methods. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://stattrek.com **Tags:** websites, science-research, scientific-method ### 5. sciencebuddies.org Science Buddies is a nonprofit site offering hundreds of science project ideas, experiments, and step-by-step guides to help students plan investigations, formulate hypotheses, and present their findings. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://sciencebuddies.org **Tags:** websites, science-research, scientific-method ### 6. jmp.com/doe JMP’s Design of Experiments (DOE) resource explains core DOE concepts and shows how to plan, analyze, and interpret experiments using JMP software. It includes tutorials, examples, and workflows for factorial, fractional factorial, response surface, and other DOE designs. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://jmp.com/doe **Tags:** websites, technology-computer-science, statistics-data-science ## Courses ### 1. Statistics with R University of Colorado Boulder course, taught by Charlie Nuttelman, that uses R and RStudio for applied statistics. Covers descriptive statistics, probability distributions, confidence intervals, one- and two-sample hypothesis tests, regression and ANOVA, so learners can run and interpret standard analyses in R. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.coursera.org/learn/statistics-and-data-analysis-with-r **Tags:** courses, science-research, scientific-method ### 2. Experimental Design Basics This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use the principles taught in the course arise in all aspects of today’s industrial and business environment. Applications from various fields will be illustrated throughout the course. Computer software packages (JMP, Design-Expert, Minitab) will be used to implement the methods presented and will be illustrated extensively. All experiments are designed experiments; some of them are poorly designed, and others are well-designed. Well-designed experiments allow you to obtain reliable, valid results faster, easier, and with fewer resources than with poorly-designed experiments. You will learn how to plan, conduct and analyze experiments efficiently in this course. **Difficulty:** Beginner | **Language:** English | **Duration:** 4 weeks of study, 4-8 hours/week | **Price:** Free **Link:** https://www.coursera.org/learn/introduction-experimental-design-basics **Tags:** courses, science-research, scientific-method ## Books ### 1. Design and Analysis of Experiments **Author:** Douglas C. Montgomery Douglas C. Montgomery's standard graduate textbook on designing and analyzing experiments, covering factorial and fractional factorial designs, response surface methodology, and ANOVA, widely used in engineering and industrial statistics courses. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0471157465?tag=edmonddante07-20 **Tags:** books, science-research, scientific-method ### 2. Experimental Design for the Life Sciences **Author:** Graeme D. Ruxton and Nick Colegrave Graeme Ruxton and Nick Colegrave's introduction to designing biological experiments, covering sample size, replication, randomization, and common statistical pitfalls, aimed at life-science students and researchers planning their first independent studies. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/019928511X?tag=edmonddante07-20 **Tags:** books, science-research, scientific-method ### 3. Field Experiments **Author:** Alan S. Gerber and Donald P. Green Alan Gerber and Donald Green's textbook on designing and analyzing randomized field experiments in the social sciences, covering random assignment, treatment effects, statistical power, and common threats to a study's validity. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0393979954?tag=edmonddante07-20 **Tags:** books, mathematics-statistics, statistics-and-probability ### 4. Statistics for Experimenters **Author:** George E. P. Box, William G. Hunter, J. Stuart Hunter A foundational text on planning and analyzing experiments, covering factorial and fractional factorial designs, response surface methods, and empirical model building. Uses worked examples and elementary mathematics to teach practical experimental design skills to scientists and engineers. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0471093157?tag=edmonddante07-20 **Tags:** books, science-research, scientific-method --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/experimental-design