<P> A distinction can be made between state problems and process problems . State problems aim to answer what the state of a phenomenon is at a given time, while process problems deal with the change of phenomena over time . Examples of state problems are the level of mathematical skills of sixteen - year - old children or the level, computer skills of the elderly, the depression level of a person, etc . Examples of process problems are the development of mathematical skills from puberty to adulthood, the change in computer skills when people get older and how depression symptoms change during therapy . </P> <P> State problems are easier to measure than process problems . State problems just require one measurement of the phenomena of interest, while process problems always require multiple measurements . Research designs such as repeated measurements and longitudinal study are needed to address process problems . </P> <P> In an experimental design, the researcher actively tries to change the situation, circumstances, or experience of participants (manipulation), which may lead to a change in behavior or outcomes for the participants of the study . The researcher randomly assigns participants to different conditions, measures the variables of interest and tries to control for confounding variables . Therefore, experiments are often highly fixed even before the data collection starts . </P> <P> In a good experimental design, a few things are of great importance . First of all, it is necessary to think of the best way to operationalize the variables that will be measured, as well as which statistical methods would be most appropriate to answer the research question . Thus, the researcher should consider what the expectations of the study are as well as how to analyse any potential results . Finally, in an experimental design the researcher must think of the practical limitations including the availability of participants as well as how representative the participants are to the target population . It is important to consider each of these factors before beginning the experiment . Additionally, many researchers employ power analysis before they conduct an experiment, in order to determine how large the sample must be to find an effect of a given size with a given design at the desired probability of making a Type I or Type II error . </P>

By definition nonexperimental research is different from experimental research in that