Testing hypotheses
In this section, we will review hypothesis testing, which is a statistical method that’s used to make inferences about population parameters based on sample data. It involves formulating two competing hypotheses – the null hypothesis (
) and the alternative hypothesis (
) – and then using sample data to determine which hypothesis is more likely to be true.
The null hypothesis, or what I like to call “business as usual,” is the default assumption or status quo for any given scenario. It’s also often considered the “least interesting” scenario. For example, if I want to test whether or not changing my sneakers makes me a better runner, the sneakers not affecting my running abilities is the null hypothesis since there is no significant difference, effect, or relationship between the variables. Oftentimes, researchers are interested in rejecting the null hypothesis.
The alternative hypothesis is the opposite...
