课程信息
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100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

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

完成时间大约为16 小时

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

英语(English)

字幕:英语(English)

您将学到的内容有

  • Check

    Ask better questions in empirical research

  • Check

    Design more informative studies

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    Evaluate the scientific literature taking bias into account

  • Check

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

您将获得的技能

Computational ReproducibilityMeta-AnalysisExperimental DesignStatistical InferencesPhilosophy of Science

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

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

完成时间大约为16 小时

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

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 2 小时

Module 1: Improving Your Statistical Questions

3 个视频 (总计 40 分钟), 2 个阅读材料, 3 个测验
3 个视频
Lecture 1.2: Do You Really Want to Test a Hypothesis?15分钟
Lecture 1.3: Risky Predictions12分钟
2 个阅读材料
Download Course Materials and Course Structure (Must Read)10分钟
Assignment 1.1: Testing Range Predictions30分钟
3 个练习
Consent Form for Use of Data10分钟
Welcome: Short Survey5分钟
Answer Form Assignment 1.1: Testing Range Predictions2分钟
2
完成时间为 3 小时

Module 2: Falsifying Predictions

3 个视频 (总计 46 分钟), 3 个阅读材料, 3 个测验
3 个视频
Lecture 2.2: Setting the Smallest Effect Size Of Interest14分钟
Lecture 2.3: Falsifying Predictions in Practice15分钟
3 个阅读材料
Assignment 2.1: The Small Telescopes Approach to Setting a SESOI30分钟
Assignment 2.2: Setting the SESOI Based on Resources30分钟
Assignment 2.3: Equivalence Testing30分钟
3 个练习
Answer Form Assignment 2.1: Setting the Smallest Effect Size Of Interest8分钟
Answer Form Assignment 2.2: Setting the SESOI Based on Resources10分钟
Answer Form Assignment 2.3: Equivalence Testing18分钟
3
完成时间为 3 小时

Module 3: Designing Informative Studies

3 个视频 (总计 48 分钟), 2 个阅读材料, 2 个测验
3 个视频
Lecture 3.2: Power Analysis12分钟
Lecture 3.3: Simulation15分钟
2 个阅读材料
Assignment 3.1: Confidence Intervals for Standard Deviations30分钟
Assignment 3.2: Power Analysis for ANOVA Designs1小时
2 个练习
Answer Form Assignment 3.1: Confidence Intervals for Standard Deviations12分钟
Answer Form Assignment 3.2: Power Analysis for ANOVA Designs20分钟
4
完成时间为 3 小时

Module 4: Meta-Analysis and Bias Detection

3 个视频 (总计 48 分钟), 4 个阅读材料, 3 个测验
3 个视频
Lecture 4.2: Intro to Meta-Analysis17分钟
Lecture 4.3: Bias Detection15分钟
4 个阅读材料
Assignment 4.1: Likelihood of Significant Findings30分钟
Assignment 4.2: Introduction to Meta-Analysis30分钟
Assignment 4.3: Detecting Publication Bias45分钟
Assignment 4.4: Checking Your Stats10分钟
3 个练习
Answer Form Assignment 4.1: Likelihood of Significant Findings14分钟
Answer Form Assignment 4.2: Introduction to Meta-Analysis4分钟
Answer Form Assignment 4.3: Detecting Publication Bias14分钟
4.9
7 条评论Chevron Right

来自Improving Your Statistical Questions的热门评论

创建者 LPOct 31st 2019

Daniel's second course as good as the first. He does a nice job!!

讲师

Avatar

Daniel Lakens

Associate Professor
Department of Human-Technology Interaction

关于 埃因霍温科技大学

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....

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  • 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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