# Bayes Theorem Calculator

If you’re feeling a bit lost, read this introduction to Bayes Theorem, which shows when and where to use the Math.

## Comparing Two Hypotheses

You’ve seen your colleague, Alice, be late 3 days, and on time 4 days the past week.

Hypothesis: They’re almost always late, i.e. they’re late 95% of the time.

Alternate Hypothesis: They’re almost never late, i.e they’re late about 5% of the time.

\[ Posterior \hspace{2mm} Odds = Prior \hspace{2mm} Odds * Likelihood \hspace{2mm} Odds\]

Main Hypothesis success rate | % |

Alternative hypothesis success rate | % |

Number of Successes | |

Number of Failures | |

Total | |

Likelihood Ratio (rounded) |

Everyone has their own prior odds. I used 1:1 for the being late case. But, you can play around with these too.

Prior Odds | : |

Posterior Odds |

In the being late example, this gives us that our current hypothesis is \(\frac{1}{19}\) times likely as the other one.

## Comparing Two Hypotheses - known likelihoods

Prior Odds | : |

Likelihood Odds | : |

Posterior Odds |

## Comparing infinite Hypotheses

To come soon.

Have another use case I’m not covering? Let me know.

Interested in learning more?

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