Understanding Bayesian Inference
Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available.
Here's the basic formula: \( P(H|E) = \frac{P(E|H) \cdot P(H)}{P(E)} \)
This approach is useful in various fields, including machine learning, data analysis, and even froge 🐸 behavior prediction!
Why Use Bayesian Inference?
- It allows for the incorporation of prior knowledge.
- Provides a probabilistic approach to inference.
- Helpful in small sample sizes or evolving datasets.