BIOSTAT

Techniques that allow us to make inferences about a population based on data that we gather from a sample.

Study results will vary from sample to sample strictly due to random chance (i.e., sampling error)

Allow us to determine how likely it is to obtain a set of results from a single sample.

This is also known as testing for "statistical significance”.

The product of hypothesis testing via various statistical tests and is claimed to be significant.

The value 0.05 is arbitrary.

Demonstrates the probability of making a type I error.

It say nothing about what the size of an effect is or what that effect size is likely to be on the total population.

A drawback is that a-priori power calculations do not take variation of data into account.

This will help avoid too many subjects being recruited for a study.