About this Course

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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. 15 hours to complete

Suggested: 5 weeks of study, 2 - 4 hours/week...

English

Subtitles: English

What you will learn

  • Check

    Ask better questions in empirical research

  • Check

    Design more informative studies

  • Check

    Evaluate the scientific literature taking bias into account

  • Check

    Reflect on current norms, and how you can improve your research practices

Skills you will gain

Computational ReproducibilityMeta-AnalysisExperimental DesignStatistical InferencesPhilosophy of Science

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

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

Approx. 15 hours to complete

Suggested: 5 weeks of study, 2 - 4 hours/week...

English

Subtitles: English

Instructor

Instructor rating5/5 (5 Ratings)Info
Image of instructor, Daniel Lakens

Daniel Lakens 

Associate Professor
Department of Human-Technology Interaction
33,437 Learners
2 Courses

Offered by

Eindhoven University of Technology logo

Eindhoven University of Technology

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Module 1: Improving Your Statistical Questions

2 hours to complete
3 videos (Total 40 min), 2 readings, 3 quizzes
3 videos
Lecture 1.2: Do You Really Want to Test a Hypothesis?15m
Lecture 1.3: Risky Predictions12m
2 readings
Download Course Materials and Course Structure (Must Read)10m
Assignment 1.1: Testing Range Predictions30m
3 practice exercises
Consent Form for Use of Data10m
Welcome: Short Survey5m
Answer Form Assignment 1.1: Testing Range Predictions2m
Week
2

Week 2

3 hours to complete

Module 2: Falsifying Predictions

3 hours to complete
3 videos (Total 46 min), 3 readings, 3 quizzes
3 videos
Lecture 2.2: Setting the Smallest Effect Size Of Interest14m
Lecture 2.3: Falsifying Predictions in Practice15m
3 readings
Assignment 2.1: The Small Telescopes Approach to Setting a SESOI30m
Assignment 2.2: Setting the SESOI Based on Resources30m
Assignment 2.3: Equivalence Testing30m
3 practice exercises
Answer Form Assignment 2.1: The Small Telescopes Approach to Setting a SESOI8m
Answer Form Assignment 2.2: Setting the SESOI Based on Resources10m
Answer Form Assignment 2.3: Equivalence Testing18m
Week
3

Week 3

3 hours to complete

Module 3: Designing Informative Studies

3 hours to complete
3 videos (Total 48 min), 2 readings, 2 quizzes
3 videos
Lecture 3.2: Power Analysis12m
Lecture 3.3: Simulation15m
2 readings
Assignment 3.1: Confidence Intervals for Standard Deviations30m
Assignment 3.2: Power Analysis for ANOVA Designs1h
2 practice exercises
Answer Form Assignment 3.1: Confidence Intervals for Standard Deviations12m
Answer Form Assignment 3.2: Power Analysis for ANOVA Designs20m
Week
4

Week 4

3 hours to complete

Module 4: Meta-Analysis and Bias Detection

3 hours to complete
3 videos (Total 48 min), 4 readings, 3 quizzes
3 videos
Lecture 4.2: Intro to Meta-Analysis17m
Lecture 4.3: Bias Detection15m
4 readings
Assignment 4.1: Likelihood of Significant Findings30m
Assignment 4.2: Introduction to Meta-Analysis30m
Assignment 4.3: Detecting Publication Bias45m
Assignment 4.4: Checking Your Stats10m
3 practice exercises
Answer Form Assignment 4.1: Likelihood of Significant Findings14m
Answer Form Assignment 4.2: Introduction to Meta-Analysis4m
Answer Form Assignment 4.3: Detecting Publication Bias14m
4.9
12 ReviewsChevron Right

Top reviews from Improving Your Statistical Questions

By SSJan 3rd 2020

Excellent! Would like only one addition, and that's a more extensive exercise on simulating data with general linear models

By SWJan 1st 2020

Cracking - very informative, nice mixture of modes of learning, and engaging

Frequently Asked Questions

  • 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.

  • 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.

  • 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.