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Michael Shields
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/y73k4z/uncertainty
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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?
Read more
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?
Read more
Scientific Inquiry
In this module, you will be introduced to the fundamentals of scientific inquiry. What makes an investigation scientific? How do we tell the difference between a scientific and a non-scientific inquiry?
Scientific Method & the Research Process
In this module, you will be introduced to the different methods of inquiry, most notably the scientific method. You will learn the terminology used in scientific inquiries and define hypotheses and theories. You will learn the steps of the research process and how the research process is scientific.
Uncertainty & Probability
In this module, you will learn about the different types of uncertainty and how these uncertainties are modeled. You will learn some fundamentals in probability theory, specifically conditional probabilities and Bayes’ Rule, necessary to understand how uncertainty is modeled.
Research as an Exercise in Uncertainty Quantification (UQ)
In this module, you will learn how the research process relates to uncertainty quantification. You will learn how to pose the research process through Bayesian hypothesis testing. You will learn how to develop a hypothesis and design a plan to test it using UQ methods.
Good to know
Good to know
Know what's good ,
what to watch for , 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
Save this course
Save Uncertainty and Research to your list so you can find it easily later:
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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
Show steps
Expand your understanding of research methods by reading a comprehensive textbook that covers a range of qualitative and quantitative approaches.
Show steps
-
Read selected chapters that align with the course topics.
-
Take notes and summarize key concepts.
Attend a Research Methods Workshop
Show steps
Gain hands-on experience and in-depth knowledge by attending a workshop led by experts in research methodology.
Browse courses on
Research Methods
Show steps
-
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
Show steps
Review the different research methodologies and their applications to gain a foundational understanding of the course content.
Browse courses on
Research Methods
Show steps
-
Read the introductory chapters of a textbook on research methods.
-
Attend a workshop or seminar on research design.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Probability and Bayes' Rule
Show steps
Enhance your understanding of probability and Bayes' Rule by following online tutorials and practicing exercises.
Browse courses on
Probability Theory
Show steps
-
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
Show steps
Engage with peers to discuss research ideas, share insights, and provide feedback, fostering a collaborative learning environment.
Browse courses on
Scientific Research
Show steps
-
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
Show steps
Reinforce your understanding of hypothesis testing by solving a variety of practice exercises.
Browse courses on
Hypothesis Testing
Show steps
-
Practice formulating hypotheses and research questions.
-
Solve exercises on hypothesis testing using different statistical methods.
Experiment with Uncertainty Quantification
Show steps
Start an experiment using the Uncertainty Quantification framework as introduced in the course.
Browse courses on
Uncertainty Quantification
Show steps
-
Choose a Research Question
-
Develop a Hypothesis
-
Design an Experiment to Test your Hypothesis
-
Collect Data
-
Analyze Data
Research Proposal Outline
Show steps
Develop a strong foundation for your research by outlining a research proposal that incorporates the principles of scientific inquiry and hypothesis testing.
Browse courses on
Research Proposal
Show steps
-
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
Show steps
Gain practical experience and contribute to the research community by participating in an open-source research project.
Browse courses on
Open Source
Show steps
-
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.
Exploring Research Methods by Paul Babie
Show steps
Expand your understanding of research methods by reading a comprehensive textbook that covers a range of qualitative and quantitative approaches.
Show steps
Show steps
Show steps
- Read selected chapters that align with the course topics.
- Take notes and summarize key concepts.
Attend a Research Methods Workshop
Show steps
Gain hands-on experience and in-depth knowledge by attending a workshop led by experts in research methodology.
Browse courses on
Research Methods
Show steps
Show steps
Show steps
- 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
Show steps
Review the different research methodologies and their applications to gain a foundational understanding of the course content.
Browse courses on
Research Methods
Show steps
Show steps
Show steps
- Read the introductory chapters of a textbook on research methods.
- Attend a workshop or seminar on research design.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Probability and Bayes' Rule
Show steps
Enhance your understanding of probability and Bayes' Rule by following online tutorials and practicing exercises.
Browse courses on
Probability Theory
Show steps
Show steps
Show steps
- 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
Show steps
Engage with peers to discuss research ideas, share insights, and provide feedback, fostering a collaborative learning environment.
Browse courses on
Scientific Research
Show steps
Show steps
Show steps
- 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
Show steps
Reinforce your understanding of hypothesis testing by solving a variety of practice exercises.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Practice formulating hypotheses and research questions.
- Solve exercises on hypothesis testing using different statistical methods.
Experiment with Uncertainty Quantification
Show steps
Start an experiment using the Uncertainty Quantification framework as introduced in the course.
Browse courses on
Uncertainty Quantification
Show steps
Show steps
Show steps
- Choose a Research Question
- Develop a Hypothesis
- Design an Experiment to Test your Hypothesis
- Collect Data
- Analyze Data
Research Proposal Outline
Show steps
Develop a strong foundation for your research by outlining a research proposal that incorporates the principles of scientific inquiry and hypothesis testing.
Browse courses on
Research Proposal
Show steps
Show steps
Show steps
- 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
Show steps
Gain practical experience and contribute to the research community by participating in an open-source research project.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- 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 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.
Statistician
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.
Risk Manager
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.
Operations Research Analyst
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.
Actuary
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.
Data Scientist
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.
Economist
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.
Market Researcher
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.
Research Scientist
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.
Public Policy Analyst
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.
Business Analyst
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.
Software Engineer
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.
Financial Analyst
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.
Consultant
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.
Epidemiologist
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.
For more career information including salaries, visit:
OpenCourser.com/course/y73k4z/uncertainty
Reading list
We've selected 15 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Uncertainty and Research.
This classic work provides a thorough examination of the scientific method and the principles of scientific inquiry. It offers valuable insights into the nature of scientific research and how to conduct it effectively.
Provides a comprehensive overview of Bayesian data analysis, covering both theoretical foundations and practical applications. It valuable resource for understanding the Bayesian approach to uncertainty quantification and hypothesis testing.
Focuses specifically on uncertainty quantification, providing a detailed treatment of the mathematical and computational methods used in this field. It useful reference for understanding the advanced techniques and applications of uncertainty quantification.
Provides a comprehensive overview of probabilistic graphical models, which are a powerful tool for representing and reasoning about uncertainty. It valuable resource for understanding the theoretical foundations and practical applications of probabilistic graphical models in the context of uncertainty quantification and hypothesis testing.
Provides a comprehensive overview of Bayesian reasoning and machine learning. It valuable resource for understanding the theoretical foundations of Bayesian reasoning and how it can be applied to problems in uncertainty quantification and machine learning.
Provides a comprehensive overview of causal inference in statistics. It valuable resource for understanding the concepts and methods of causal inference and how to apply them to problems in uncertainty quantification and hypothesis testing.
Provides a practical guide to Bayesian data analysis using the JAGS software package. It valuable resource for understanding the basics of Bayesian modeling and how to apply it to problems in uncertainty quantification and hypothesis testing.
Provides practical advice on writing scientific papers, including how to structure a paper, write clear and concise prose, and present data effectively. It valuable resource for students and researchers who need to communicate their research findings effectively.
Provides a comprehensive overview of statistical learning methods, including both supervised and unsupervised learning. It valuable resource for understanding the theoretical foundations and practical applications of statistical learning in the context of uncertainty quantification.
Provides a comprehensive overview of information theory, inference, and learning algorithms. It valuable resource for understanding the theoretical foundations of information theory and how it can be applied to problems in uncertainty quantification and machine learning.
Provides a practical introduction to Bayesian statistics using the R and Stan software packages. It valuable resource for understanding the basics of Bayesian modeling and how to apply it to problems in uncertainty quantification and hypothesis testing.
Is an excellent introduction to probability theory, providing a clear and accessible explanation of the fundamental concepts and principles. It useful reference for understanding the mathematical foundations of uncertainty quantification.
Provides a comprehensive overview of uncertainty in artificial intelligence. It valuable resource for understanding the different types of uncertainty that arise in AI systems and how to deal with them.
Provides an introduction to reinforcement learning, a powerful technique for learning how to make decisions in uncertain environments. It valuable resource for understanding the basic concepts and applications of reinforcement learning in the context of uncertainty quantification and optimal decision-making.
Covers a wide range of research methods used in the social sciences, including both quantitative and qualitative approaches. It provides practical guidance on designing and conducting research studies, and useful reference for understanding the different research methods available.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/y73k4z/uncertainty
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Johns Hopkins University
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Michael Shields
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Good to know
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
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