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.
Offered By
Improving your statistical inferences
About this Course
Learner Career Outcomes
10%
17%
10%
Skills you will gain
Learner Career Outcomes
10%
17%
10%
100% online
Flexible deadlines
Intermediate Level
Approx. 22 hours to complete
English
Syllabus - What you will learn from this course
Introduction + Frequentist Statistics
Likelihoods & Bayesian Statistics
Multiple Comparisons, Statistical Power, Pre-Registration
Effect Sizes
Reviews
4.9
TOP REVIEWS FROM IMPROVING YOUR STATISTICAL INFERENCES
Excellent course. The lecturer has written code snippets that let the students visualize the meaning and interrelationship of p-values confidence-intervals power effect-size bayesian-inference.
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
This is a top-notch course. The ground (especially pitfalls) is very well covered, and useful free tools are engaged (R, G*Power, prof's own spreadsheets for calculating effect size).
This course changed my concepts not only about statistics but about research and science. Daniel Lakens is a fantastic lecturer and scientist. I can't recommend this course enough.
Offered by
Eindhoven University of Technology
Eindhoven University of Technology (TU/e) is a research-driven, design-oriented university of technology with a strong international focus. The university was founded in 1956, and has around 8,500 students and 3,000 staff. TU/e has defined strategic areas focusing on the societal challenges in Energy, Health and Smart Mobility. The Brainport Eindhoven region is one of world’s smartest; it won the title Intelligent Community of the Year 2011.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
In which languages is this course available?
All videos have English and Chinese subtitles. the assignments are only available in English.
More questions? Visit the Learner Help Center.
