Chapter 3: Continuous Random Variables

Journey from discrete to continuous probability distributions

Key Concepts You'll Master

Probability Density

Probability per unit interval

\(f(x)\)

Integration

Finding area under curves

\(\int_{a}^{b} f(x)dx\)

Normal Distribution

The bell curve

\(\mathcal{N}(\mu, \sigma^2)\)

Exponential

Waiting time distribution

\(\lambda e^{-\lambda x}\)

The Continuous Revolution

Move beyond counting to measuring. Continuous distributions open up a world of infinite possibilities, from the ubiquitous normal distribution to exponential waiting times. Master integration, probability density, and the tools that power modern statistics and machine learning.

Chapter 3: Continuous Random Variables - Learning Hub

Master Continuous Random Variables

From discrete counts to continuous measurements

All sections are accessible - follow the numbered sequence for the best learning experience

Overall Progress

0%

Learning Progress0/10

Choose Your Learning Path

Start Here

Interactive Formula Builder

Build formulas step-by-step

Master continuous distribution formulas by building them interactively. Click on each part to understand why it's there and how it works.

Key topics:

  • Probability density function f(x)
  • Cumulative distribution function F(x)
  • Normal distribution formula N(μ,σ²)

Introduction: Bridge to Continuous

From discrete to continuous

Make the conceptual leap from discrete to continuous distributions. Understand probability density and area under curves.

Key topics:

  • Transition from PMF to PDF
  • Understand probability as area
  • Visualize continuous distributions
Complete prerequisites first

3.1 Probability Density Functions

PDFs and integration

Master probability density functions and calculate probabilities through integration. Interactive visualizations make calculus intuitive.

Key topics:

  • Define and work with PDFs
  • Calculate probabilities via integration
  • Find cumulative distribution functions
Recommended after prerequisites
Complete prerequisites first

3.2 Expectation & Variance

Continuous E[X] and Var(X)

Calculate expected values and variance for continuous distributions using integration. Build intuition through visualizations.

Key topics:

  • Calculate E[X] = ∫xf(x)dx
  • Find variance using E[X²]
  • Apply continuous transformations
Recommended after prerequisites
Complete prerequisites first

3.3 Normal Distributions

The bell curve and z-scores

Master the most important continuous distribution. Learn z-scores, empirical rule, and normal table lookups through interactive tools.

Key topics:

  • Understand normal distribution properties
  • Calculate and interpret z-scores
  • Apply the empirical rule (68-95-99.7)
Recommended after prerequisites
Complete prerequisites first

3.4 Exponential Distributions

Modeling waiting times

Model continuous waiting times with the exponential distribution. Explore memoryless property and connections to Poisson.

Key topics:

  • Derive exponential PDF
  • Understand rate parameter λ
  • Apply memoryless property
Recommended after prerequisites
Complete prerequisites first

3.5 Gamma Distributions

Generalized waiting times

Extend exponential to model waiting for multiple events. Master shape and scale parameters through visualization.

Key topics:

  • Understand gamma function Γ(α)
  • Work with shape and scale parameters
  • See exponential as special case
Recommended after prerequisites
Complete prerequisites first

3.6 Joint Distributions

Multiple random variables

Extend to multiple continuous variables. Master joint PDFs, marginal distributions, and conditional distributions.

Key topics:

  • Work with joint PDFs f(x,y)
  • Calculate marginal distributions
  • Find conditional distributions
Recommended after prerequisites
Complete prerequisites first

3.7 Normal Approximation

Central Limit Theorem preview

See how discrete distributions approach normal for large n. Apply continuity correction for better approximations.

Key topics:

  • Apply normal approximation to binomial
  • Use continuity correction
  • Check approximation conditions
Recommended after prerequisites
Complete prerequisites first

Bonus: Double Integral Calculator

Interactive integration tool

Master double integrals for joint distributions. Visualize numerical integration step-by-step with different methods and see how probabilities are calculated over regions.

Key topics:

  • Understand double integration visually
  • Compare Riemann sum methods
  • Calculate probabilities over regions
Recommended after prerequisites

Learning Tips

Build Intuition First

Start with fundamentals to understand the core concepts

Practice Real Scenarios

Apply concepts to real-world data to reinforce understanding

Master the Concepts

Learn when and how to apply each concept effectively