--- title: Control Groups description: This core component of experimental design isolates the effects of an independent variable by establishing a baseline for comparison. Learners will understand how to select, manage, and analyze control groups to validate causal relationships in scientific studies. category: sciences subcategory: scientific-method difficulty: beginner, intermediate, advanced url: /subject/control-groups --- # Control Groups This core component of experimental design isolates the effects of an independent variable by establishing a baseline for comparison. Learners will understand how to select, manage, and analyze control groups to validate causal relationships in scientific studies. ## Available Resources 1 Books • 2 Courses • 5 Websites • 1 Papers ## Websites ### 1. Understanding Science A free UC Berkeley Museum of Paleontology site explaining how science actually works: testing ideas against evidence, designing controlled experiments, peer review, and common misconceptions. Readers learn to distinguish scientific explanations from untested claims and judge how studies use controls. **Difficulty:** Beginner | **Price:** Free **Link:** https://undsci.berkeley.edu/ **Tags:** scientific-method, experimental-design, control-groups, hypothesis-testing, nature-of-science ### 2. NIST/SEMATECH e-Handbook of Statistical Methods A free online statistics reference produced by NIST with SEMATECH, covering process characterization, control charts, capability analysis, reliability, and design of experiments. Includes worked case studies and Dataplot code, so you can apply each method to real measurement data. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.itl.nist.gov/div898/handbook/ **Tags:** statistics, process-control, control-charts, design-of-experiments, reliability ### 3. Randomization (J-PAL Research Resources) The operational half of the topic that textbooks skip: how you physically construct the control group, what to do when strata do not divide evenly, whether to randomize individuals or clusters, and how to interpret a failed balance test. Practitioner guide to assigning units between treatment and control: simple, permuted and stratified randomization, choosing the unit of assignment, handling misfits and spillovers, checking baseline balance, and reproducible Stata code for each step. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://www.povertyactionlab.org/resource/randomization **Tags:** randomization, randomized-controlled-trials, stratification, cluster-randomization, development-economics ### 4. 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 ### 5. seeing-theory.brown.edu Seeing Theory is an interactive, browser-based resource from Brown University that uses visual simulations to explain fundamental probability and statistics concepts. It offers interactive demos and explanations on topics like probability, distributions, sampling, the central limit theorem, confidence intervals, hypothesis testing, and Bayesian reasoning. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://seeing-theory.brown.edu **Tags:** websites, technology-computer-science, data-science--ai ## Courses ### 1. Designing Studies Learn how to design effective studies with control groups! Created by Sal Khan and team. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.khanacademy.org/math/statistics-probability/designing-studies **Tags:** study-design, experimental-design, control-groups, sampling, statistics ### 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. Experimental and Quasi-Experimental Designs for Generalized Causal Inference **Author:** William R. Shadish, Thomas D. Cook, Donald T. Campbell The standard reference on field experimentation, cataloguing threats to internal, external, construct and statistical-conclusion validity, and mapping which design (randomized, regression-discontinuity, interrupted time series, non-equivalent control group) rules out which threat. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0395615569?tag=edmonddante07-20 **Tags:** causal-inference, quasi-experiments, validity, research-design, field-experiments ## Papers ### 1. Understanding and Misunderstanding Randomized Controlled Trials **Author:** Angus Deaton, Nancy Cartwright Working-paper version of the Social Science and Medicine article arguing that randomization does not automatically balance covariates in finite samples, that trial results need not transfer to other populations, and where control groups mislead. **Difficulty:** Advanced | **Language:** English | **Price:** Free **Link:** https://www.princeton.edu/~deaton/downloads/Deaton_Cartwright_RCTs_with_ABSTRACT_August_25.pdf **Tags:** randomized-controlled-trials, causal-inference, external-validity, evidence-based-policy, philosophy-of-science --- *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/control-groups