How Does Frequentist vs Bayesian Thinking Work?

Imagine you're trying to guess how many jellybeans are in a jar, that’s like frequentist and bayesian thinking working side by side!

Let's say you want to know how many jellybeans are in the jar. A frequentist is like your friend who takes out 10 jellybeans, counts them, puts them back, and repeats this over and over, they’re trying to figure out the average number of jellybeans in the whole jar by seeing what happens every time.

On the other hand, a bayesian is more like you, you might already think there are about 50 jellybeans based on how big the jar looks. Then, when you take out 10 jellybeans and count them, you update your guess: "Okay, so maybe it's closer to 60!" You're using what you already knew (your prior) and adding new information (data) to make a better guess.

Frequentists are like detectives who look at the whole case from all angles, they just need a lot of clues. Bayesians are more like detectives who start with a clue or two, then keep adding more as they go along, it’s like solving a mystery step by step!

Both ways help you figure things out, but one uses all the clues right away, and the other adds them piece by piece. Imagine you're trying to guess how many jellybeans are in a jar, that’s like frequentist and bayesian thinking working side by side!

Frequentists are like detectives who look at the whole case from all angles, they just need a lot of clues. Bayesians are more like detectives who start with a clue or two, then keep adding more as they go along, it’s like solving a mystery step by step!

Both ways help you figure things out, but one uses all the clues right away, and the other adds them piece by piece.