A Brief Introduction to Bayesian Data Analysis

These flashcards cover essential vocabulary and concepts related to Bayesian data analysis derived from the lecture notes.

Bayesian Analysis

A statistical method that incorporates prior beliefs and evidence to update the probability for a hypothesis as more evidence becomes available.

Null Hypothesis Significance Testing (NHST)

A method that determines the likelihood that an observed effect in the data occurred by chance, often used in hypothesis testing.

Priors

Initial assumptions made about a situation, which reflect beliefs or knowledge before observing data.

Posterior Probability

The probability of a model after observing the data, calculated by combining the prior with the likelihood of the observed data.

Likelihood

The probability of the observed data under a particular model or hypothesis.

Cone of Uncertainty

A method used in forecasting to represent the uncertainty in prediction about the future path of a storm, such as a hurricane.

Bernoulli Process

A statistical model representing a sequence of experiments with two possible outcomes (success/failure), commonly used for binary data.

Iterative Testing

A method of testing where results are evaluated at multiple stages, allowing for adjustments in data collection based on preliminary findings.

Historical Tracking Map

A representation that shows the paths of storms over time, used to analyze past hurricane movements and behaviors.

Storm Category

A classification for hurricanes based on their wind speeds, ranging from tropical depressions to category 5 storms.