Have you ever ever wondered if a change to your website or marketing strategy truly makes a difference? 🤔 On this guide, I’ll show you how one can use hypothesis testing to make data-driven decisions with confidence.
In data analytics, hypothesis testing is continuously used when running A/B tests to check two versions of a marketing campaign, webpage design, or product feature to make data-driven decisions.
- The means of hypothesis testing
- Several types of tests
- Understanding p-values
- Interpreting the outcomes of a hypothesis test
Hypothesis testing is a way to make a decision whether there’s enough evidence in a sample of information to support a specific belief in regards to the population. In easy terms, it’s a way to check if a change you made has an actual effect or if any difference is just on account of probability.
