Project:Sandbox

Hypothesis testing for  equity  returns
What is hypothesis testing?

Hypothesis testing in statistics is a way for you to test the results of a survey or experiment to see if you have meaningful results. You’re basically testing whether your results are valid by figuring out the odds that your results have happened by chance. If your results may have happened by chance, the experiment won’t be repeatable and so has little use. The methodology employed by the analyst depends on the nature of the data used and the reason for the analysis. Hypothesis testing is used to infer the result of a hypothesis performed on sample data from a larger population.

How hypothesis testing works

In hypothesis testing, an analyst tests a statistical sample, with the goal of accepting or rejecting a null hypothesis. The test tells the analyst whether or not his primary hypothesis is true. If it isn't true, the analyst formulates a new hypothesis to be tested, repeating the process until data reveals a true hypothesis. First steps to keep in mind before starting hypothesis testing: State a  null  hypothesis

State an  alternative  hypothesis


 * Think about  which  test  to  use
 * Select the  appropriate  confidence  level


 * Step 1
 * select the  sample  size


 * Step 2
 * calculate the  rejection  region  using  the  appropriate  statistics  table



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