Improving Your Statistical Questions from Coursera

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.

What's inside

Syllabus

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? What are different types of questions we can ask? Which question does a hypothesis test really answer, and is this answer actually what you are interested in, or is the question you are asking more about exploration, description, or prediction? How can we make riskier predictions than null-hypothesis tests, and why is this useful?

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.

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.

Module 4: Meta-Analysis and Bias Detection

Regrettably we work in a scientific enterprise where the published literature does not reflect real research. Publication bias and selection biases lead to a scientific literature that can’t be interpreted without taking these biases into account. We will discuss what real research lines look like, and how to meta-analytically evaluate the literature while keeping bias in mind.

Module 5: Computational Reproducibility, Philosophy of Science, and Scientific Integrity

We discuss three last topics. First, we will make sure other people can use your data to ask new questions, by making sure your data analysis is computationally reproducible. Then, we will reflect on how your philosophy of science influences the types of questions you will ask, and what you value as you do research. Finally, we discuss scientific integrity, and reflect on why our research practice is not always aligned with the best possible ways to provide reliable answers to scientific questions.

Module 6: Final Exam

This module contains a graded exam. It covers content from the entire course. We recommend making this exam only after you went through all the other modules.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides learners with techniques and tools that are immediately applicable to their research

Emphasizes the importance of designing informative studies and justifying error rates

Addresses the issue of publication bias and provides strategies for evaluating the literature accordingly

Emphasizes the importance of computational reproducibility and scientific integrity

Taught by Daniel Lakens, who is recognized for his work in statistical inference

Suitable for researchers who want to improve their statistical questioning and research practices

Reviews summary

Positive: thought provoking review

Learners say this course goes over important concepts that are very useful to researchers. Many learners note how thought provoking this course was. This course is well connected and well structured. Learners note that it was challenging, but worthwhile. Learners also note that this course may not be appropriate for all learners wanting to update statistical questions.

This course covers important concepts.

"It covers so many important things to me in science."

"This is an excellent statistics course for anybody who wants to apply hypothesis testing correctly (e.g. for research projects in social sciences)."

"Well connected and inspired course."

This course is well structured.

"The quality of the course was truly worth a five-star rating."

"This is an excellent statistics course for anybody who wants to apply hypothesis testing correctly (e.g. for research projects in social sciences)."

"Well connected and inspired course."

This course is very useful for researchers.

"Fantastic state-of-the-art and practical knowledge. It is very useful for researchers at any stage of the scientific career."

"as usual. I was suitable only for two tailed NHST without any direction of effect."

"The only problem is some modules are similar to previous MOOC but slightly different, and sometimes it is confussing."

This course is thought provoking.

"This was the best course that I have ever taken. Professor Lakens's excellent expression and wonderful lesson plan have created a thought-provoking review."

"The sections on philosophy of science also help in this respect as they shed a light on the kinds of questions experimenters ask."

"I believe that this second course from Daniel Lakens is one of the "must take" classes offered via Coursera."

This course is challenging.

"Way too hard for those who want to update statistical question asking, not modeling, simulations, meta-analysis, etc. "

"The only problem is some modules are similar to previous MOOC but slightly different, and sometimes it is confussing."

"This is an excellent statistics course for anybody who wants to apply hypothesis testing correctly (e.g. for research projects in social sciences)."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Improving Your Statistical Questions with these activities:

Review Pre-Calculus Concepts

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Ensure you have a strong foundation in pre-calculus concepts to fully grasp the statistical methods taught in this course.

Browse courses on Pre-Calculus

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Review your notes from a previous pre-calculus course.
Take practice quizzes and exams to test your understanding.

Review: Thinking Statistically

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Gain a foundation in statistical thinking and learn how to apply it to real-world problems.

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Read the book and take notes on the key points.
Work through the practice problems in the book.
Apply what you have learned to a real-world dataset.

Join a Study Group for the Course

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Enhance your understanding by working with peers and get support from others taking the course.

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Find a study group that fits your schedule and learning style.
Attend study group meetings regularly and participate actively.
Work together on assignments and projects.

Five other activities

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Show all eight activities

Practice Hypothesis Testing with Null Hypothesis Tests

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Improve your ability to specify your statistical questions and design informative studies.

Browse courses on Hypothesis Testing

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Review the syllabus for the online course and try to identify the concepts mentioned in this activity.
Take notes on the key points of hypothesis testing and null hypothesis tests.
Work through practice problems on hypothesis testing and null hypothesis tests.
Apply what you have learned to a real-world dataset.

Attend a Workshop on Data Visualization

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Enhance your ability to present data and communicate research findings effectively.

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Find a workshop on data visualization that fits your schedule and interests.
Register for the workshop and attend all sessions.
Participate actively in the workshop and ask questions.

Create a Blog Post on a Statistical Concept

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Develop your understanding of statistical concepts through teaching others.

Browse courses on Statistical Concepts

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Choose a statistical concept that you are familiar with.
Research the concept and gather information from reliable sources.
Write a blog post that explains the concept in a clear and concise way.
Share your blog post with others and get feedback.

Conduct a Meta-Analysis to Evaluate Scientific Literature

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Build your skills in evaluating scientific literature while keeping biases in mind.

Browse courses on Meta-Analysis

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Identify a research question that you are interested in.
Search for and collect relevant studies.
Extract data from the studies and assess their quality.
Conduct a meta-analysis to synthesize the findings of the studies.
Interpret the results of the meta-analysis and draw conclusions.

Design and Implement a Statistical Study

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Apply the statistical methods you learn in the course to a real-world problem and complete a hands-on project.

Browse courses on Data Analysis

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Identify a research question that you are interested in.
Design a statistical study to answer your research question.
Collect data and analyze it using appropriate statistical methods.
Write a report on your findings.

Career center

Learners who complete Improving Your Statistical Questions will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data. This course can help Statisticians by providing them with the skills to design informative studies, make predictions, and communicate findings to others. These skills are essential for conducting high-quality statistical research and providing insights to stakeholders.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help Data Analysts by providing them with the skills to justify error rates, perform meta-analyses, and detect publication bias. These skills are essential for conducting rigorous data analysis and providing insights to stakeholders.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use scientific methods to extract knowledge and insights from data. This course can help Data Scientists by providing them with the skills to design informative studies, perform meta-analyses, and detect publication bias. These skills are essential for conducting rigorous data analysis and providing insights to stakeholders.

See salaries and explore the career path for Data Scientist

Data Engineer

Data Engineers design, build, and maintain data systems. This course can help Data Engineers by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for developing high-quality data systems and ensuring that data is accurate and reliable.

See salaries and explore the career path for Data Engineer

Actuary

Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course can help Actuaries by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and providing insights to insurance companies and other organizations.

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Risk Manager

Risk Managers identify, assess, and mitigate risks to organizations. This course can help Risk Managers by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and developing effective risk management strategies.

See salaries and explore the career path for Risk Manager

Epidemiologist

Epidemiologists investigate the causes of disease and other health problems in populations. This course can help Epidemiologists by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and developing public health interventions.

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Policy Analyst

Policy Analysts develop and evaluate policies to address public problems. This course can help Policy Analysts by providing them with the skills to design informative studies, evaluate findings in the literature, and communicate their findings to policymakers. These skills are essential for conducting high-quality research and developing effective policies.

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Economist

Economists study the production, distribution, and consumption of goods and services. This course can help Economists by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and providing insights to policymakers and businesses.

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Biostatistician

Biostatisticians apply statistical methods to solve problems in biology and medicine. This course can help Biostatisticians by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and providing insights to healthcare professionals.

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Market Researcher

Market Researchers collect and analyze data to understand consumer behavior and market trends. This course can help Market Researchers by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and providing insights to businesses.

See salaries and explore the career path for Market Researcher

Researcher

Researchers conduct studies to answer questions and contribute to new knowledge. This course can help Researchers by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and communicating findings to others.

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Scientist

Scientists work in a variety of fields, using scientific methods to conduct research and develop new knowledge. This course can help Scientists by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and communicating findings to others.

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Financial Analyst

Financial Analysts evaluate the financial performance of companies and make investment recommendations. This course can help Financial Analysts by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and providing insights to investors.

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Professor

Professors teach and conduct research at colleges and universities. This course can help Professors by providing them with the skills to design informative studies, evaluate findings in the literature, and make their analyses computationally reproducible. These skills are essential for conducting high-quality research and teaching students about statistical methods.

See salaries and explore the career path for Professor