Whether you're in a lab, a tech firm, or manufacturing, how you set up an experiment is often more important than how you analyze the data. Bad design leads to "noise" that no amount of fancy math can fix.
Groups similar experimental units together to cancel out known sources of variation (like different batches of raw materials). 3. Noise vs. Signal
If you don't design with the analysis in mind, you're just collecting anecdotes. Good DOE turns "I think this works" into "I have 95% confidence this works."