Controlling Variables and Experimental Design
Variable control is absolutely crucial for getting reliable results in psychology experiments. There are several types of extraneous variables that can mess up your findings if you're not careful.
Confounding variables are outside factors that accidentally influence your results. You can reduce these by using controlled laboratory settings, though this might make your experiment feel a bit artificial. Participant variables relate to individual differences between people - things like age, personality, or background that could skew results.
The three main experimental designs each have their trade-offs. Repeated measures uses the same participants in all conditions, which is efficient but can create order effects (people getting tired or better with practice). Independent groups uses different people for each condition, avoiding order effects but introducing participant variables. Matched pairs tries to get the best of both worlds by carefully pairing similar participants.
Quick Tip: Remember that counterbalancing (splitting participants and reversing the order of tasks) is your best friend for dealing with order effects in repeated measures designs.
