Question

Explain the difference between coorelational, quasi-experimental, and true-experimental designs.

Answer 1

Correlational and experimental studies-

An experiment isolates and manipulates the independent variable to observe its effect on the dependent variable, and controls the environment in order that extraneous variables may be eliminated. Experiments establish cause and effect.

A correlation identifies variables and looks for a relationship between them. An experiment tests the effect that an independent variable has upon a dependent variable but a correlation looks for a relationship between two variables.

This means that the experiment can predict cause and effect (causation) but a correlation can only predict a relationship, as another extraneous variable may be involved that it not known about.

True experimental design and quasi experimental design-

Quasi-Experimental Research

First let's look at quasi-experimental research. Quasi-experimental means that the research will include features of a true experiment but some elements may be missing. The most common experimental element to be missing is a random sample. A random sample occurs when every individual in the group being studied has an equal chance of being selected. Without a random sample, it is more difficult to demonstrate cause and effect links in research.

Even with the possibility of interpretation problems, in human growth and development research, quasi-experimental research is a common and often necessary replacement for a true experiment. This is usually because it is not practical or ethical to utilize a random sample. For example, imagine trying to create a random sample for a study on the effects of child abuse among single parents. If a person is randomly selected from a group of single parents to be part of the experimental group, they will be forced to abuse their children throughout the study. This would definitely not be acceptable!

Quasi-experimental research cannot illustrate cause and effect relationships as accurately as a controlled experiment. However, cause and effect relationships can be inferred from the data. Just keep in mind that there can be a larger margin of error for these assumptions, and that the margin of error can vary between studies.

TRUE EXPERIMENTAL DESIGN-

A true experiment is a type of experimental design and is thought to be the most accurate type of experimental research. This is because a true experiment supports or refutes a hypothesis using statistical analysis. A true experiment is also thought to be the only experimental design that can establish cause and effect relationships. So, what makes a true experiment?

There are three criteria that must be met in a true experiment

1. Control group and experimental group
2. Researcher-manipulated variable
3. Random assignment

Let's look at each of these requirements more closely.

Control Group and Experimental Group

True experiments must have a control group, which is a group of research participants that resemble the experimental group but do not receive the experimental treatment. The control group provides a reliable baseline data to which you can compare the experimental results. The experimental group is the group of research participants who receive the experimental treatment. True experiments must have at least one control group and one experimental group, though it is possible to have more than one experimental group.

Researcher-Manipulated Variable

In true experiments, the researcher has to change or manipulate the variable that is hypothesized to affect the outcome variable that is being studied. The variable that the researcher has control over is called the independent variable. The independent variable is also called the predictor variable because it is the presumed cause of the differences in the outcome variable.

The outcome or effect that the research is studying is called the dependent variable. The dependent variable is also called the outcome variable because it is the outcome that the research is studying. The researcher does not manipulate the dependent variable.

Random Assignment

Research participants have to be randomly assigned to the sample groups. In other words, each research participant must have an equal chance of being assigned to each sample group. Random assignment is useful in that it assures that the differences in the groups are due to chance. Research participants have to be randomly assigned to either the control or experimental group.

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