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.
Improving your statistical inferencesEindhoven University of Technology
About this Course
Skills you will gain
Eindhoven University of Technology
Eindhoven University of Technology (TU/e) is a young university, founded in 1956 by industry, local government and academia. Today, their spirit of collaboration is still at the heart of the university community. We foster an open culture where everyone feels free to exchange ideas and take initiatives.
- 5 stars88.64%
- 4 stars9.86%
- 3 stars0.94%
- 2 stars0.27%
- 1 star0.27%
TOP REVIEWS FROM IMPROVING YOUR STATISTICAL INFERENCES
Solid course which taught me how to interpret p-values in a variety of contexts and taught me to not just to consider but (systematic and practical) ways of how to correct for publication bias.
Excellent course with a lot to learn. After 10 years in data analysis it provided me with great new insights and material to further improve my skills and understanding of data analysis
Excellent course. The materials were well laid out and explained in an accessible but thorough manner. I've already begun using what I've learned in my current work.
Great course! Highly recommended.
One thing to improve - I would like to see more theory behind the different effect sizes (eta-squared/omega squared/etc)
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