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Bias Mitigation

8 resources

Level
Type

📹Videos(1)

video👁️ 0

Why Most Published Research Findings Are False

John Ioannidis talk on publication bias and other issues in scientific method, top comment link in r/statistics

beginner🇬🇧

🎓Courses(2)

course👁️ 0

Reproducible Research

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.

intermediate🇬🇧
course👁️ 1

Improving your statistical inferences

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles. In practical, hands on assignments, you will learn how to simulate t-tests to learn which p-values you can expect, calculate likelihood ratio's and get an introduction the binomial Bayesian statistics, and learn about the positive predictive value which expresses the probability published research findings are true. We will experience the problems with optional stopping and learn how to prevent these problems by using sequential analyses. You will calculate effect sizes, see how confidence intervals work through simulations, and practice doing a-priori power analyses. Finally, you will learn how to examine whether the null hypothesis is true using equivalence testing and Bayesian statistics, and how to pre-register a study, and share your data on the Open Science Framework. All videos now have Chinese subtitles. More than 30.000 learners have enrolled so far! If you enjoyed this course, I can recommend following it up with me new course "Improving Your Statistical Questions"

intermediate🇬🇧

🌐Websites(5)

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website👁️ 0

Your Bias

Interactive guide to cognitive biases with mitigation strategies, practitioner rec in r/cogsci

beginner🇬🇧
website👁️ 0

Center for Open Science

Free resources on preregistration, badges, and TOP guidelines to mitigate researcher bias

beginner🇬🇧
website👁️ 0

explorable.com

Explorable.com provides accessible tutorials and explanations across psychology, statistics, and research methods, with articles on cognitive biases, experimental design, and practical techniques for bias mitigation.

intermediate🇬🇧
website👁️ 0

sciencebuddies.org

ScienceBuddies.org is a student-focused science education site offering hundreds of hands-on project ideas with step-by-step instructions, materials lists, and guidance for planning, conducting, and reporting experiments. It provides topic-specific ideas and teacher resources to help learners master the scientific method and science fair prep.

intermediate🇬🇧
website👁️ 0

nature.com

Nature.com is the online platform for Nature and its family of scientific journals, offering peer‑reviewed research articles, reviews, and news across the sciences. It also features commentary, policy and ethics coverage, and content on issues like bias, reproducibility, and diversity in research.

intermediate🇬🇧

Frequently Asked Questions

What are the best free resources to learn Bias Mitigation?

Dantes has curated 5 resources for Bias Mitigation, including 1 videos, 2 courses, 2 websites. All resources are hand-picked for quality — no algorithmic filler. Browse the full list above to find the format that works best for you.

Is Bias Mitigation hard to learn?

Bias Mitigation is approachable at the beginner level — there are resources here specifically for those starting from scratch. As you progress, intermediate and advanced material is also available to take your skills further.

What types of Bias Mitigation learning resources are available on Dantes?

For Bias Mitigation, Dantes has curated 1 videos, 2 courses, 2 websites. Each resource type serves a different learning style: videos and YouTube for visual learners, books for depth, courses for structured progression, and websites for quick reference.

How does Dantes select Bias Mitigation resources?

Dantes is an algorithm-free learning directory. Resources are hand-curated based on quality, accuracy, and usefulness — not engagement metrics or paid placements. The goal is to surface the best learning material for Bias Mitigation, whether it's a free YouTube series, a classic textbook, or an open courseware from a top university.

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