Uncertainty and Research from Coursera

This course teaches the fundamentals of scientific research. We approach the research process as a means of systematically reducing uncertainty and demonstrate how conducting a scientific investigation can be posed as an exercise in Bayesian uncertainty quantification. We begin by exploring the scientific landscape to understand the different types of research, where they are conducted, how they are supported, and why each of these types of research is important. We then formalize scientific inquiry and the scientific method and elaborate the research process and its scientific merits. Basic concepts in probability theory are introduced leading to a conceptually simple presentation of Bayes’ Rule. We then illustrate how Bayes’ Rule provides a mathematical framework for the research process. We place an emphasis on the role that research plays in our daily and professional lives and how research skills can help us think critically, whether you’re in a technical field or not. Exercises are designed to help you improve your research skills and think more scientifically.

Learners who are new to research fields or would like to improve their research skills in any field for career/professional or personal growth are encouraged to enroll. The course is taught at an introductory level such that, by the end of the course, you will be able to formulate a research hypothesis and devise a scientific research plan to test that hypothesis. To be successful in this course, you will need entrance-level college mathematics.

What's inside

Syllabus

Introduction to the Research Landscape

In this module, you will be introduced to the landscape of scientific research. Why do we perform research? Who conducts research and where do they conduct it? What different kinds of research are undertaken? Why are the various types of research important?

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches the fundamentals of scientific research, including hypothesis formulation and research plan design

Explores the scientific landscape, which is standard in research fields

Taught by Michael Shields, who are recognized for their work in research

Develops critical thinking skills, which are core skills in any field

Provides a strong foundation for beginners in scientific research

Requires entrance-level college mathematics, which may be a barrier for some learners

Reviews summary

Foundations in scientific research and uncertainty

According to students, this course offers a solid foundation in scientific research, presenting it as an exercise in Bayesian uncertainty quantification. Learners appreciate the clear explanation of complex concepts like Bayes' Rule and its practical application to critical thinking skills, relevant for both professional growth and personal development. The course's well-structured modules and introductory level make it accessible for those new to research, though a basic understanding of college-level mathematics is essential. Some emphasize the course's unique approach to formalizing scientific inquiry through a quantitative lens.

Well-organized modules that guide learners through complex topics.

"I found the course modules very well-structured, making it easy to follow the progression."

"Each section built clearly upon the last, which was helpful for understanding complex ideas."

"I liked how the syllabus flows logically from basic concepts to advanced applications."

Develops practical skills for daily and professional critical thinking.

"I can apply the critical thinking skills learned here to my professional life immediately."

"This course helped me develop a more scientific approach to problems in my daily life."

"The exercises were great for improving my research planning and critical analysis."

Introduces Bayes' Rule as a framework for research and UQ.

"The explanation of Bayes' Rule and its application to research was a highlight for me."

"I appreciated learning how to systematically reduce uncertainty using Bayesian principles."

"I found this course offers a unique perspective on research through uncertainty quantification."

Provides a strong introductory framework for scientific inquiry.

"As someone new to research, I found this course incredibly helpful in understanding the basics."

"I found it lays a clear groundwork for scientific inquiry and critical thinking."

"The course really helped me grasp the fundamentals of research methodology."

Requires basic college-level math, potentially challenging for some.

"While introductory, some of the math concepts, especially probability, were a bit challenging without a fresh background."

"I recommend having a solid grasp of entrance-level college mathematics for this course."

"I found the mathematical explanations could be a bit dense at times, requiring re-reads."

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 Uncertainty and Research with these activities:

Exploring Research Methods by Paul Babie

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Expand your understanding of research methods by reading a comprehensive textbook that covers a range of qualitative and quantitative approaches.

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Read selected chapters that align with the course topics.
Take notes and summarize key concepts.

Attend a Research Methods Workshop

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Gain hands-on experience and in-depth knowledge by attending a workshop led by experts in research methodology.

Browse courses on Research Methods

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Research and identify a reputable workshop that aligns with your learning goals.
Attend the workshop and actively participate in discussions and exercises.

Explore Different Types of Research

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Review the different research methodologies and their applications to gain a foundational understanding of the course content.

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Read the introductory chapters of a textbook on research methods.
Attend a workshop or seminar on research design.

Six other activities

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Probability and Bayes' Rule

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Enhance your understanding of probability and Bayes' Rule by following online tutorials and practicing exercises.

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Follow a video tutorial on the basics of probability.
Solve practice problems on probability and conditional probability.
Learn about Bayes' Rule and its applications.

Research Discussion Group

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Engage with peers to discuss research ideas, share insights, and provide feedback, fostering a collaborative learning environment.

Browse courses on Scientific Research

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Join a study group or online forum dedicated to the course topic.
Participate in discussions, share your research findings, and offer constructive feedback to others.

Hypothesis Testing Exercises

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Reinforce your understanding of hypothesis testing by solving a variety of practice exercises.

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Practice formulating hypotheses and research questions.
Solve exercises on hypothesis testing using different statistical methods.

Experiment with Uncertainty Quantification

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Start an experiment using the Uncertainty Quantification framework as introduced in the course.

Browse courses on Uncertainty Quantification

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Choose a Research Question
Develop a Hypothesis
Design an Experiment to Test your Hypothesis
Collect Data
Analyze Data

Research Proposal Outline

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Develop a strong foundation for your research by outlining a research proposal that incorporates the principles of scientific inquiry and hypothesis testing.

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Write a brief introduction and background on your chosen research topic.
Develop a clear research question and hypothesis.
Outline the methodology and data analysis plan.

Contribute to an Open-Source Research Project

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Gain practical experience and contribute to the research community by participating in an open-source research project.

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Identify an open-source research project that interests you.
Contact the project maintainers and express your interest in contributing.
Review the project documentation and codebase.
Start working on a specific task or issue.

Career center

Learners who complete Uncertainty and Research will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts collect, clean, and interpret data to help organizations make informed decisions. They use statistical methods and software to analyze data and identify trends and patterns. The Uncertainty and Research course can help Data Analysts by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with data and to make more accurate predictions.

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Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, finance, and marketing. The Uncertainty and Research course can help Statisticians by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with data and to make more accurate predictions.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical methods to solve problems in a variety of industries. They work with businesses to improve efficiency and productivity. The Uncertainty and Research course can help Operations Research Analysts by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with decision-making and to make more informed recommendations.

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Risk Manager

Risk Managers identify, assess, and manage risks for organizations. They work in a variety of industries, including finance, insurance, and healthcare. The Uncertainty and Research course can help Risk Managers by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with risk and to make more informed decisions.

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Actuary

Actuaries use mathematical and statistical methods to assess and manage risk. They work in a variety of industries, including insurance, finance, and healthcare. The Uncertainty and Research course can help Actuaries by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with risk and to make more informed decisions.

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Data Scientist

Data Scientists use mathematical and statistical methods to extract knowledge from data. They work in a variety of industries, including technology, finance, and healthcare. The Uncertainty and Research course can help Data Scientists by providing them with a strong foundation in probability theory and Bayesian statistics. This knowledge can help them to better understand the uncertainties associated with data and to make more accurate predictions.

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Software Engineer

Software Engineers design, develop, and maintain software systems. They work in a variety of industries, including technology, finance, and healthcare. The Uncertainty and Research course may be useful for Software Engineers who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about software design and development.

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Financial Analyst

Financial Analysts analyze financial data to make recommendations about investments. They work in a variety of industries, including finance, insurance, and banking. The Uncertainty and Research course may be useful for Financial Analysts who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about investments.

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Market Researcher

Market Researchers collect and analyze data to understand consumer behavior. They work in a variety of industries, including marketing, advertising, and product development. The Uncertainty and Research course may be useful for Market Researchers who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about market research.

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Epidemiologist

Epidemiologists investigate the causes of disease and injury. They work in a variety of settings, including public health departments, hospitals, and research institutions. The Uncertainty and Research course may be useful for Epidemiologists who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about disease prevention and control.

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Research Scientist

Research Scientists conduct research in a variety of fields, including science, engineering, and medicine. They work in a variety of settings, including universities, research institutes, and government agencies. The Uncertainty and Research course may be useful for Research Scientists who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about research design and analysis.

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Economist

Economists study the production, distribution, and consumption of goods and services. They work in a variety of settings, including academia, government, and the private sector. The Uncertainty and Research course may be useful for Economists who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about economic policy and forecasting.

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Public Policy Analyst

Public Policy Analysts develop and analyze public policies. They work in a variety of settings, including government agencies, think tanks, and non-profit organizations. The Uncertainty and Research course may be useful for Public Policy Analysts who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about public policy.

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Business Analyst

Business Analysts analyze business data to identify opportunities for improvement. They work in a variety of industries, including finance, consulting, and technology. The Uncertainty and Research course may be useful for Business Analysts who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about business strategy and operations.

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Consultant

Consultants provide advice and expertise to organizations on a variety of topics. They work in a variety of industries, including management, technology, and healthcare. The Uncertainty and Research course may be useful for Consultants who want to develop a better understanding of probability theory and Bayesian statistics. This knowledge can help them to make more informed decisions about consulting projects.

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