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Daniel Lakens

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Improving Your Statistical Questions

Eindhoven University of Technology

About this Course

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This course aims to help you to ask better statistical questions when performing empirical research. We will discuss how to design informative studies, both when your predictions are correct, as when your predictions are wrong. We will question norms, and reflect on how we can improve research practices to ask more interesting questions. In practical hands on assignments you will learn techniques and tools that can be immediately implemented in your own research, such as thinking about the smallest effect size you are interested in, justifying your sample size, evaluate findings in the literature while keeping publication bias into account, performing a meta-analysis, and making your analyses computationally reproducible.
If you have the time, it is recommended that you complete my course 'Improving Your Statistical Inferences' before enrolling in this course, although this course is completely self-contained.

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Intermediate Level

A basic knowledge of statistics and research methods is necessary. My previous MOOC 'Improving Your Statistical Inferences' is recommended.

Approx. 17 hours to complete

English

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What you will learn

Ask better questions in empirical research
Design more informative studies
Evaluate the scientific literature taking bias into account
Reflect on current norms, and how you can improve your research practices

Skills you will gain

Computational Reproducibility
Meta-Analysis
Experimental Design
Statistical Inferences
Philosophy of Science

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

A basic knowledge of statistics and research methods is necessary. My previous MOOC 'Improving Your Statistical Inferences' is recommended.

Approx. 17 hours to complete

English

Could your company benefit from training employees on in-demand skills?

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Instructor

Instructor rating

4.92/5 (26 Ratings)

Daniel Lakens
Top Instructor

Associate Professor

Department of Human-Technology Interaction

72,181 Learners

2 Courses

Offered by

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.

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Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Module 1: Improving Your Statistical Questions

One of the biggest improvements most researchers can make is to more clearly specify their statistical questions. When you perform a study, what is it you really want to know?

2 hours to complete

3 videos (Total 40 min), 2 readings, 3 quizzes

Week2

Week 2

4 hours to complete

Module 2: Falsifying Predictions

There is little use in making predictions if you can never be wrong - so how do we make sure your predictions are falsifiable? We discuss why falsifiable predictions are important, and how to make your predictions falsifiable in practice. One important aspect of making predictions falsifiable is to specify a range of values that is not predicted, and we will examine different approaches to specifying a smallest effect size of interest.

4 hours to complete

3 videos (Total 46 min), 3 readings, 3 quizzes

3 videos

Lecture 2.1: Falsifying Predictions in Theory16mLecture 2.2: Setting the Smallest Effect Size Of Interest14mLecture 2.3: Falsifying Predictions in Practice15m

3 readings

Assignment 2.1: The Small Telescopes Approach to Setting a SESOI30mAssignment 2.2: Setting the SESOI Based on Resources30mAssignment 2.3: Equivalence Testing30m

3 practice exercises

Answer Form Assignment 2.1: The Small Telescopes Approach to Setting a SESOI30mAnswer Form Assignment 2.2: Setting the SESOI Based on Resources30mAnswer Form Assignment 2.3: Equivalence Testing30m

Week3

Week 3

3 hours to complete

Module 3: Designing Informative Studies

If studies are designed to answer a question, you should make sure the answer you will get after collecting data is informative. Instead of mindlessly setting Type 1 and Type 2 error rates, we will learn why it is important to be able to justify error rates, and some approaches how to do so. We discuss the benefits of using your smallest effect size of interest in power analyses, and why learning to simulate data is a useful tool. Simulations can help you to improve your understanding of statistics, enable you to design informative studies, and even ask novel questions.

3 hours to complete

3 videos (Total 48 min), 2 readings, 2 quizzes

Week4

Week 4

4 hours to complete

Module 4: Meta-Analysis and Bias Detection

4 hours to complete

3 videos (Total 48 min), 4 readings, 3 quizzes

3 videos

Lecture 4.1: Mixed Results14mLecture 4.2: Intro to Meta-Analysis17mLecture 4.3: Bias Detection15m

4 readings

Assignment 4.1: Likelihood of Significant Findings30mAssignment 4.2: Introduction to Meta-Analysis30mAssignment 4.3: Detecting Publication Bias45mAssignment 4.4: Checking Your Stats10m

3 practice exercises

Answer Form Assignment 4.1: Likelihood of Significant Findings30mAnswer Form Assignment 4.2: Introduction to Meta-Analysis30mAnswer Form Assignment 4.3: Detecting Publication Bias30m

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Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Which previous knowledge is required?
The course assumes basic knowledge about statistical inferences (t-tests, ANOVA) and some knowledge of designing research studies. The course is for intermediate level. Coursera offers basic introductions to statistics (which this course is not), and my previous MOOC 'Improving Your Statistical Inferences' might be a better starting point if you lack training in statistics. You do not need knowledge programming in R - we will use it as a fancy calculator by changing code (but not programming).

More questions? Visit the Learner Help Center.

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Improving Your Statistical Questions

Improving Your Statistical Questions

About this Course

What you will learn

Skills you will gain