# In some hypothesis test, H0: µ = 12.

*Figure out the *. The alternate hypothesis is the opposite of the null hypothesis. In other words, what happens if our experiment makes a difference?

## In some hypothesis test, H1: µ 12.

### State the null and an appropriate alternal hypothesis. 5.

This is where the **alternative hypothesis** (H1) enters the scene. In an attempt to disprove a null hypothesis, researchers will seek to discover an alternative hypothesis.

### Hypothesis testing is vital to test patient outcomes.

A** logical hypothesis** is a proposed explanation possessing limited evidence. Generally, you want to turn a logical hypothesis into an empirical hypothesis, putting your theories or postulations to the test.

## The Null Hypothesis - Dailymotion Video

Traditional testing (the type you probably came across in elementary stats or AP stats) is called Non-Bayesian. It is how often an outcome happens over repeated runs of the experiment. It’s an **objective** view of whether an experiment is repeatable.

Bayesian hypothesis testing is a **subjective **view of the same thing. It takes into account how much faith you have in your results. In other words, would you wager money on the outcome of your experiment?

## Disproving the Null Hypothesis ..

It’s good science to let people know if your study results are solid, or if they could have happened by chance. The usual way of doing this is to test your results with a . A p value is a number that you get by running a hypothesis test on your data. A P value of 0.05 (5%) or less is usually enough to claim that your results are repeatable. However, there’s another way to test the validity of your results: Bayesian Hypothesis testing. This type of testing gives you another way to test the strength of your results.

## A null hypothesis | InfraCursos

Bayesian hypothesis testing helps to answer the question: *Can the results from a test or survey be repeated? *

Why do we care if a test can be repeated? Let’s say twenty people in the same village came down with leukemia. A group of researchers find that cell-phone towers are to blame. However, a second study found that cell-phone towers had nothing to do with the cancer cluster in the village. In fact, they found that the cancers were completely random. If that sounds impossible, it actually can happen! Clusters of cancer can happen . There could be many reasons why the first study was faulty. One of the main reasons could be that they just didn’t take into account that sometimes things happen randomly and we just don’t know why.