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
English
Subtitles: English

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 ReproducibilityMeta-AnalysisExperimental DesignStatistical InferencesPhilosophy of Science
Shareable Certificate
Earn a Certificate upon completion
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
English
Subtitles: English

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

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Frequently Asked Questions

  • 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.

  • 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.

  • You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

  • 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).

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