Why Hypothesis Testing is the Backbone of Data Science
Hypothesis testing is the backbone of data science because it provides a rigorous, structured way to distinguish real patterns from random noise and to make decisions backed by statistical evidence rather than intuition. It allows data scientists to validate assumptions, quantify uncertainty, and determine whether observed results are genuine or just due to chance—making it essential for trustworthy models, experiments, and business decisions. openstax
What Is Hypothesis Testing?
Hypothesis testing is a statistical method used to evaluate claims about a population using sample data. It works by setting up two mutually exclusive hypotheses: openstax
Null hypothesis (H₀): The default assumption (e.g., “There is no difference between two groups”). dasca
