Alternatives to Experimentation: Quasi-Experimental and Correlational Designs

Flashcards for reviewing key concepts related to quasi-experimental and correlational research designs.

Quasi-Experimental Designs

Research designs that evaluate causal hypotheses without full control over variables, particularly random assignment.

Pre-existing Groups

Groups that already exist in a quasi-experimental design, such as different schools or workplaces.

Non-equivalent Groups Design

A type of quasi-experimental design where groups that already exist are compared.

Causal Inference

The process of determining whether a cause-and-effect relationship exists between variables; weaker in quasi-experimental designs than in true experiments.

Correlation

A statistical relationship between two variables that does not imply causation.

Pearson’s r

A correlation coefficient that indicates the strength and direction of a linear relationship between two variables.

Operational Definition

A clear and specific definition of a variable that allows it to be measured or manipulated.

Independent Variable (IV)

The variable manipulated by the researcher to observe its effect.

Dependent Variable (DV)

The variable measured to assess the effect of the independent variable.

Null Hypothesis (H₀)

A hypothesis predicting no relationship or effect between variables.

Alternative Hypothesis

A hypothesis predicting that an effect or relationship exists between variables.

Extraneous Variables

Uncontrolled variables that could affect the outcome of an experiment.

Single-Blind Experiments

Experiments in which participants are unaware of the treatment conditions to reduce bias.

Random Assignment

The process of randomly allocating participants to different treatment conditions to minimize group differences.

Third-variable problem

The issue that an unmeasured variable may influence both variables being studied, creating a false impression of a relationship.

Directionality problem

The uncertainty regarding which variable influences the other in a correlational study.

Causal Research Designs

Research designs aimed at establishing cause-and-effect relationships by manipulating variables and controlling extraneous factors.

Experimental Group

The group in an experiment that receives the treatment or intervention being tested.

Control Group

The group in an experiment that does not receive the treatment and is used as a comparison.

Longitudinal Studies

Research designs that involve repeated observations of the same variables over long periods of time to examine changes over time.

Cross-sectional Studies

Research designs that collect data from a population at one specific point in time, allowing for comparisons between different groups.

What are the strengths of quasi-experimental designs?

Quasi-experimental designs allow researchers to evaluate causal relationships without the need for random assignment, making them useful in real-world settings where such controls are not possible.

What limitations do quasi-experimental designs have?

Quasi-experimental designs often have weaker causal inference due to potential confounding variables and the lack of random assignment.

What is the role of extraneous variables in research?

Extraneous variables can introduce bias and affect the validity of the results if not controlled for in an experiment.

What is the difference between a null hypothesis and an alternative hypothesis?

A null hypothesis predicts no effect or relationship between variables, while an alternative hypothesis suggests that a relationship does exist.

What is the significance of the Pearson’s r correlation coefficient?

Pearson's r quantifies the direction and strength of a linear relationship between two variables, helping researchers understand their association.

What are the benefits of using longitudinal studies?

Longitudinal studies provide insight into how variables change over time and allow researchers to track developmental trends and patterns.

How do cross-sectional studies compare to longitudinal studies?

Cross-sectional studies analyze data from a population at a specific point in time, whereas longitudinal studies examine changes over time with repeated observations.

What is the third-variable problem?

The third-variable problem occurs when an unmeasured variable influences both variables being studied, potentially leading to a misleading relationship.

What is the purpose of single-blind experiments?

Single-blind experiments prevent participant bias by keeping subjects unaware of which treatment they are receiving.

What is random assignment, and why is it important?

Random assignment is the process of allocating participants to treatment conditions randomly, minimizing pre-existing differences between groups to enhance the validity of the results.

What is a quasi-experimental design?

A research design that evaluates causal hypotheses without full control over variables, particularly random assignment.

What are pre-existing groups in quasi-experimental research?

Groups that already exist in a quasi-experimental design, such as different schools or workplaces.

What is the non-equivalent groups design?

A type of quasi-experimental design where groups that already exist are compared.

What is correlation in research?

A statistical relationship between two variables that does not imply causation.

What are extraneous variables?

Uncontrolled variables that could affect the outcome of an experiment.

What is a dependent variable?

The variable measured to assess the effect of the independent variable.

What is an independent variable?

The variable manipulated by the researcher to observe its effect.

What is the null hypothesis?

A hypothesis predicting no relationship or effect between variables.

What is the alternative hypothesis?

A hypothesis predicting that an effect or relationship exists between variables.

What is the significance of using control groups?

Control groups provide a baseline to compare the effects of the treatment in experimental groups.