Pseudoreplication

Pseudoreplication means pretending we have more data than we actually do. It happens when scientists make the wrong conclusion by using too few pieces of information.

Think of it like cookie baking. If we want to know which recipe makes the best chocolate chip cookies, we have to bake several batches, using the same ingredients and following the same steps. However, if we only bake one batch and divide it into several smaller pieces to taste, we might think we have several batches of cookies to try, but in fact, it's still just one batch. This is what we call pseudoreplication.

Same thing can happen in science. If a researcher wants to find out if a new medicine works, they need to test it on a group of patients who have the same illness. If the researcher only tests the medicine on one patient and takes their blood pressure before and after the medicine, they might think they have enough data to draw a conclusion. But, in reality, they only have one piece of information, which is not enough to make a proper conclusion.

In order to avoid pseudoreplication, scientists need to make sure they have enough data points that are truly independent of one another. That way, they can make accurate conclusions about their research topic.