Quantitative research uses the scientific method to evaluate theories or problems by testing specific hypotheses involving the relationship among or the differences between variables.

Quantitative research uses the scientific method to evaluate theories or problems by testing specific hypotheses involving the relationship among or the differences between variables.  The variables are measured using numerical data, allowing statistical procedures to be used for a mathematical analysis.  Many different quantitative designs exist within a basic or applied context to accurately address the purpose of the research and related research questions.

Non-Experimental (Non-Causal) Correlational Designs
A correlational design is one of the most often encountered non-experimental (non-causal) quantitative designs.  Within correlational designs, an actual experimental condition is non-existent; rather, relationships between variables are explored without a determination of causality.  These types of studies are meant to help researchers examine how two or more variables vary in conjunction with each other.  Correlational studies can help describe complex relationships among a myriad of variables and are often employed when attempting to determine how a change in one or more variables will co-vary with one or more other variables.  Within all correlational studies, causation cannot be assumed, regardless of how strong the correlational evidence.

Quasi-Experimental (Non-Randomized) Designs
Quasi-experimental designs are one of the more commonly used quantitative designs, particularly within educational research, as true randomization is unavailable in schools.  Students are enrolled and staff are chosen to be employed in schools, thus eliminating the ability of the researcher to truly randomly choose participants.  Well-designed quasi-experimental designs can often demonstrate clear causal relationships between variables with the limited possibility of error, but lack the randomization required of a true experimental design eliciting even less potential for error.

Experimental (Randomized) Designs
Randomization, or the random selection and assignment of participants based solely on chance, is the foundational element of experimental designs, reducing alternative explanations for the effects the researcher is measuring.  Random selection involves the procedure used to identify participants to be members of a sample, while random assignment involves the procedure used to assign identified participants to the various groups within a study.

Variety of Experimental Designs
A large number of experimental designs exist to address various research topics and corresponding hypotheses.  Three experimental designs commonly used in psychological research are: 1) pretest-posttest control group design, 2) time-series design (repeated measure), and 3) factorial design.