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Experimental psychology refers to work done by those who apply experimental methods to psychological study and the underlying processes. Experimental psychologists employ human participants and animal subjects to study a great many topics, including (among others) sensation, perception, memory, cognition, learning, motivation, emotion; developmental processes, social psychology, and the neural ...
Some researchers believe that a good way to increase external validity is by conducting field experiments. In a field experiment, people's behavior is studied outside the laboratory, in its natural setting. A field experiment is identical in design to a laboratory experiment, except that it is conducted in a real-life setting.
A possible cause for demand characteristics is participants' expectations that they will somehow be evaluated, leading them to figure out a way to 'beat' the experiment to attain good scores in the alleged evaluation. Rather than giving an honest answer, participants may change some or all of their answers to match the experimenter's ...
For this reason, many experiments in psychology are conducted in laboratory conditions where they can be more strictly regulated. Alternatively, some experiments are less controlled. Quasi-experiment 's are those that a researcher sets up in a controlled environment, but does not control the independent variable.
An experiment must also control the possible confounding factors—any factors that would mar the accuracy or repeatability of the experiment or the ability to interpret the results. Confounding is commonly eliminated through scientific controls and/or, in randomized experiments , through random assignment .
Use of multifactorial experiments instead of the one-factor-at-a-time method. These are efficient at evaluating the effects and possible interactions of several factors (independent variables). Analysis of experiment design is built on the foundation of the analysis of variance , a collection of models that partition the observed variance into ...
Optimal designs can accommodate multiple types of factors, such as process, mixture, and discrete factors. Designs can be optimized when the design-space is constrained, for example, when the mathematical process-space contains factor-settings that are practically infeasible (e.g. due to safety concerns).
Factor analysis can be only as good as the data allows. In psychology, where researchers often have to rely on less valid and reliable measures such as self-reports, this can be problematic. Interpreting factor analysis is based on using a "heuristic", which is a solution that is "convenient even if not absolutely true". [49]