Accessible Tools

Learn to use indicator variables, simple functions, and Bayes’ theorem without any special mathematical background or training

Practical Application

Apply Bayesian reasoning to clinical work, making decisions with precision and coherence

Hands-On Learning

Compute everything by hand, on paper, or in your head; no computer required. This is Bayes on a napkin

About the Course

Uncertainty is a common occurrence in behavioral health. This course equips you with the tools to make decisions under uncertainty using Bayesian reasoning. Explore the fundamentals of probability, translating clinical events into indicators, altering treatment beliefs with Bayes’ theorem, and interpreting clinical scores, all through real-world examples from therapy and case management.

Meet Your Instructor

Hi, I'm Dr. Shane Sparkes. I'm a psychotherapist with a PhD in Biostatistics. I bring over twelve years of experience in behavioral health to this course. I've worked as a clinician providing intensive wrap-around services to individuals who experience high acuity behavioral health disorders in complicated, field-based settings. Join me on a journey to master Bayesian reasoning in behavioral health. I'm excited to share my expertise and guide you through practical applications of probability in clinical practice. No special mathematical competency or background are needed. I value easy, intuitive applications since I know what is possible in or between sessions. Bring a pencil, scrap paper, and a willingness to achieve a higher level of coherence and transparency in clinical decision making.

Course Curriculum

8 Chapters · 36 Lessons

    1. 1.1: Uncertainty is a Medium of Care Free preview
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      1.2: Probability as Personal, Informed Belief

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      1.3: The Basic Setup — Events and Sample Spaces

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      Assignment 1: Outcomes and Events in Your Practice

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      Practice Quiz

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      2.1: The Yes/No Switch

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      2.2: Defining Indicators in Practice

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      Assignment 2: Define Your Own Indicators

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      Practice Quiz

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      3.1: What Makes Something a Probability?

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      3.2: Two Useful Consequences

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      3.3: Coherence — Why the Rules Matter

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      Assignment 3: Check Your Coherence

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      Practice Quiz

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      4.1: The Logic of “Given That”

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      4.2: Independence — When Knowing One Thing Does Not Alter Knowledge About Another

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      Assignment 4: Conditional Reasoning in Your Caseload

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      Practice Quiz

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      5.1: Flipping the Direction of Conditioning

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      5.2: A Clinical Bayesian Reasoning Example

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      5.3: Sequential Updating — Learning Over the Course of Care

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      Assignment 5: Practice Bayesian Updating

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      Practice Quiz

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      6.1: Simple Functions

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      6.2: Expected Value — The Probability-Weighted Average

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      6.3: Conditional Expected Values

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      Assignment 6: Build a Clinical Score from Indicators

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      Practice Quiz

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      7.1: A Complete Clinical Example

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      7.2: Measuring Improvement from Baseline

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      7.3: What This Approach Gives You

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      Assignment 7: Apply Bayesian Reasoning to a Case

    5. (Included in full purchase)

      Practice Quiz

    1. (Included in full purchase)

      Course Exam

    2. (Included in full purchase)

      References

    3. (Included in full purchase)

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