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
- 5 stars88.53%
- 4 stars9.86%
- 3 stars1.06%
- 2 stars0.26%
- 1 star0.26%
TOP REVIEWS FROM IMPROVING YOUR STATISTICAL INFERENCES
Excellent course. Must take for any students interested in doing scientific research, especially in the domain of the social sciences. Very interesting and informative.
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)
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 explanations. Strong examples. Helpful exercises. Highly recommended for anyone who ever has to conduct inferential statistics or read anything that reports a p value or bayes factor.
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