What steps are crucial for ensuring validity in hypothesis testing?
In the realm of Business Intelligence (BI), the validity of hypothesis testing is the bedrock of data-driven decision-making. Ensuring that the conclusions drawn from data are reliable requires a structured approach to hypothesis testing. Whether you're evaluating market trends, customer behavior, or operational efficiency, each step in the process must be executed with precision to avoid costly errors and misinterpretations. Let's explore the crucial steps you need to take to guarantee the validity of your hypothesis tests.