There are 2 ways to explain Hypothesis Testing – there’s the hard and fast truth, and then there’s the slow and subtle way.
Allow me to hit you first with the hard and fast truth, before I take it slow and subtle.
For the hard and fast truth, Investopedia defines hypothesis testing as:
Hypothesis testing is used to infer the result of a hypothesis performed on sample data from a larger population. The test tells the analyst whether or not his primary hypothesis is true. Statistical analysts test a hypothesis by measuring and examining a random sample of the population being analyzed.
Now if you got lost there somewhere in that complex explanation, that’s because it is complex.
Traditional Statisticians, Data Scientists, Mathematicians, and Lean Six Sigma practicioners tend to use a lot of jargon.
But the truth is, it’s just because they know what these terms mean and it’s just part of their vocabulary when they talk to each other.
But thankfully, for the uninitiated, as well as those who are still outside of the “statistically significant” circle, there’s a slow and subtle way to explain hypothesis testing.
Allow me to break it down for you in Simple terms and give you an example.
Continue reading “What is Hypothesis Testing – Explained in Simple Terms?”
