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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.Here, the researcher does not want to miss a potentially interesting relation and therefore aims to minimize the probability of rejecting a real effect or relation; this probability is sometimes referred to as β and the associated error is of type II.
Therefore, experiments are often highly fixed even before the data collection starts.
In a good experimental design, a few things are of great importance.
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.
State problems are easier to measure than process problems.
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.
A research design is a framework that has been created to find answers to research questions. Nonetheless, the list below offers a number of useful distinctions between possible research designs.
A research design is an arrangement of conditions or collection. In fixed designs, the design of the study is fixed before the main stage of data collection takes place.
Non-experimental research designs can be broadly classified into three categories.
First, in relational designs, a range of variables are measured.