Improving Your Statistical Questions
Master advanced statistical research methods and design more informative studies. Learn meta-analysis, bias detection, and computational reproducibility.
Master advanced statistical research methods and design more informative studies. Learn meta-analysis, bias detection, and computational reproducibility.
This comprehensive course focuses on enhancing statistical research methodology and experimental design skills. Students learn to formulate better statistical questions, design more informative studies, and evaluate scientific literature while accounting for bias. The course covers advanced topics including falsifiable predictions, power analysis, meta-analysis, and computational reproducibility. Through practical assignments and hands-on exercises, participants develop skills in setting effect sizes, justifying sample sizes, and implementing reproducible analyses. Special emphasis is placed on understanding publication bias, detecting research biases, and maintaining scientific integrity.
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What you'll learn
Ask better questions in empirical research
Design more informative studies with proper error rates
Evaluate scientific literature accounting for bias
Conduct meta-analyses and detect publication bias
Make analyses computationally reproducible
Apply philosophical principles to research practice
Skills you'll gain
This course includes:
3.7 Hours PreRecorded video
12 assignments
Access on Mobile, Desktop
FullTime access
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There are 6 modules in this course
The course teaches advanced statistical methodology and research design principles. Students learn to formulate better research questions, design more informative studies, and critically evaluate scientific literature. The curriculum covers crucial topics including falsifiable predictions, power analysis, meta-analysis, and computational reproducibility. Through hands-on assignments, participants develop practical skills in setting effect sizes, conducting power analyses, and implementing reproducible research practices.
Module 1: Improving Your Statistical Questions
Module 1 · 1 Hours to complete
Module 2: Falsifying Predictions
Module 2 · 3 Hours to complete
Module 3: Designing Informative Studies
Module 3 · 3 Hours to complete
Module 4: Meta-Analysis and Bias Detection
Module 4 · 4 Hours to complete
Module 5: Computational Reproducibility, Philosophy of Science, and Scientific Integrity
Module 5 · 3 Hours to complete
Module 6: Final Exam
Module 6 · 52 Minutes to complete
Fee Structure
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Instructor
Innovator in Meta-Science and Research Methods
Dr. Daniel Lakens is an Associate Professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), where he specializes in meta-science, research methods, and applied statistics. His empirical research primarily explores conceptual thought, similarity, and meaning, while also focusing on the design and interpretation of studies, as well as the development of reward structures within scientific research. Dr. Lakens is committed to enhancing the reliability and efficiency of psychological science, evidenced by his work funded by an NWO VIDI grant aimed at improving research practices. He has been instrumental in advocating for replication research and has co-edited a special issue on pre-registered studies with Brian Nosek. A passionate educator, he teaches an online MOOC titled "Improving Your Statistical Inferences," which has attracted thousands of learners. Recognized for his contributions to open science, Dr. Lakens has conducted over 40 workshops on improving research methodologies and was awarded the TU/e Teacher of the Year in 2014. Through his innovative approaches to research and education, Dr. Lakens continues to influence the landscape of scientific inquiry, promoting transparency and rigor in the field of psychology.
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