Identify and briefly explain with examples five types of non-experimental designs discussed in the course.

Single Variable Research Design

Single variable research design focuses on only one variable as opposed to how two or more variables statistically differ from each other. Research employing this design does not address statistical relationships, which makes it unpopular.

Correlational Research Design

The correlational research design involves the investigators comparing two variables in which they are interested and then assessing their relationship without having to control the extraneous variables. For example, a researcher can be studying the relationship between a student’s self-esteem after being bullied. Thus, the researcher is looking to find out how bullying and self-esteem are related.

Quasi-Experimental Research Design

The quasi-experimental research design involves the researcher manipulating the study’s independent variables with a keen avoidance of assigning conditions or order of conditions to their participants. For example, a researcher can carry out a controlled study comparing the incidence of bullying in two different schools, one with an anti-bullying program and the other without.

Qualitative Research Design

In qualitative research design, researchers deal with non-numerical data, which they can analyze without using statistical techniques. For example, a researcher can study clients’ experiences in a psychiatric ward, and the analysis can comprise a description of these experiences with examples. Therefore, the qualitative research design’s findings are gathered in a written format without adopting any statistical approaches.

Factorial Design

In factorial research design, the investigators combine many single-variable designs into one and then examine the treatment of variations for efficiency.

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