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  • Confidence Bootcamp
    • My learning
    • Intro to experimentation
      • Introduction
      • Lesson 1: Why you should experiment
      • Lesson 2: Experiment hypothesis
      • Lesson 3: Success and guardrail metrics
      • Lesson 4: Success metrics
      • Lesson 5: Set up your experiment
      • Lesson 6: Calculation frequency
      • Lesson 7: Target audience
      • Lesson 8: Sample size
      • Lesson 9: Quality assurance
      • Lesson 10: Run your experiment
      • Lesson 11: Evaluate your experiment and make a decision
      • Lesson 12: A/B tests and rollouts
      • Course wrap up
    • Intro to metrics
      • Introduction
      • Lesson 1: What is a metric?
      • Lesson 2: Metric roles
      • Lesson 3: Time considerations
      • Lesson 4: Capturing behavior
      • Lesson 5: Strategic metrics
      • Lesson 6: Interpretability
      • Lesson 7: Feasibility and sensitivity
      • Lesson 8: Variance reduction
      • Lesson 9: Select metrics
      • Lesson 10: Segment-level analysis
      • Course wrap up
    • Scientific product development
      • Introduction
      • Lesson 1: Why you should experiment
      • Lesson 2: The scientific method
      • Lesson 3: Randomized controlled trials
      • Lesson 4: Experiment hypothesis
      • Lesson 5: Case study
        • Case study
        • Answers to case study
      • Lesson 6: Why do we need statistics?
      • Lesson 7: Success metrics
      • Lesson 8: Detectable effects and sample size
      • Lesson 9: Make a decision
      • Course wrap up
    • A primer on hypothesis testing
      • Introduction
      • Lesson 1: Introduction to hypothesis testing
      • Lesson 2: True vs estimated effects
      • Lesson 3: Sampling distribution of the difference-in-means estimator
      • Lesson 4: Z-tests and how to reject the null hypothesis
      • Lesson 5: False postive rate and alpha
      • Lesson 6: True positive rate, MDE, and power
      • Course wrap up
    • Intro to Feature Flags
      • Introduction
      • Lesson 1: What is a feature flag?
      • Lesson 2: Lifecycle of a feature flag
      • Lesson 3: Clients
      • Lesson 4: Evaluation context and targeting
    • Sample size calculation - I
      • Introduction
      • Lesson 1: What is the required sample size?
      • Lesson 2: Alpha and power
      • Lesson 3: Baseline mean and variance
      • Lesson 4: Sample size playground - I
    • Sample size calculation - II
      • Introduction
      • Lesson 1: Multi-metric decision making
      • Lesson 2: Number of success metrics
      • Lesson 3: Number of guardrail metrics
      • Lesson 4: Number of comparisons
      • Lesson 5: Sample size playground - II
    • Sample size calculation - III
      • Introduction
      • Lesson 1: Binary metrics
      • Lesson 2: Treatment group proportions
      • Lesson 3: Variance reduction
      • Lesson 4: Sequential testing and sample size
      • Lesson 5: Sample size playground - III
    • Advance your experimentation
      • Introduction
      • Lesson 1: Guardrail metrics with non-inferiority margins
      • Lesson 2: Choose evaluation frequency
      • Lesson 3: Metrics' roles in experiments
      • Lesson 4: Cumulative holdback evaluations
    • Experimentation culture
      • Introduction
      • Lesson 1: Onboarding into experimentation
      • Lesson 2: Empowering experimentation champions
      • Lesson 3: Sustaining the experimentation culture
    • Videos

Videos

A/B Tests and Rollouts in Product Development

Learn about how experimentation tools like A/B tests and rollouts are used in product development with concrete examples in 3 minutes and 28 seconds.

Alpha and Power

Learn about the statistical settings alpha and power and how to set them in your experiment in 4 minutes and 30 seconds.

Evaluation Frequency

Learn about the analysis methods used for different evaluation frequencies and their pros and cons in 2 minutes and 15 seconds.

Minimum Detectable Effect

Learn about the Minimum Detectable Effect (MDE) and how to set it in your experiment in 3 minutes and 43 seconds.

Non-Inferiority Margin

Learn about the Non-Inferiority Margin (NIM) and how to set it in your experiment in 3 minutes and 44 seconds.

Control your Product with Feature Flags

This video gives a quick overview of how you can allow Confidence to control parts of your application using feature flags in 2 minutes and 10 seconds.

From Events to Metric Results

This video gives a quick overview of how you go from tracking events in your application to seeing results on the Confidence results page in 3 minutes and 17 seconds.

How to Think About Time in Metrics

This video explains how to reason about time when defining metrics in Confidence and helps you choose whether to use a time window in your metrics and whether to include users in your metrics cumulatively in 4 minutes and 34 seconds.

Targeting and Evaluation Context

This video gives a quick overview of how to increase the flexibility of who you can include and exclude in your experiments by providing more information when you resolve feature flags in 2 minutes and 10 seconds.

Surfaces in Confidence

This video introduces surfaces and how you can use them to streamline experimentation in Confidence. You learn how to organize, coordinate, and configure experiments with surfaces in 3 minutes and 26 seconds.

Access Control in Confidence

This video gives a quick overview of how to control who can see and change what in Confidence with fine-grained permissions in 3 minutes and 21 seconds.

Introduction to Experiment Coordination with Exclusivity Groups and Holdbacks

This video introduces the concepts of exclusive groups and holdbacks, and how you can use them to control which experiments overlap and which do not in 3 minutes and 57 seconds.

Advanced Experiment Coordination

This video gives examples and builds intuition for advanced experiment coordination using exclusivity groups and holdbacks across multiple surfaces in 4 minutes and 47 seconds.

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