Research Methods: Variables and Study Design

• A research hypothesis predicts the impact of changing the independent variable (IV) on the dependent variable (DV).
• A research hypothesis should include the IV, the DV, the predicted direction of the effect, and both IV conditions.

Variables

• The independent variable (IV)is manipulated.
• The dependent variable (DV) is measured.

Allocation

• Allocation refers to how participants are assigned to control and experimental groups.
• The control group provides a baseline for comparison to determine if the IV affects the DV.

Extraneous and Confounding Variables

• Extraneous variables are any variables other than the IV that may affect the DV, causing unwanted effects on results.
• A confounding variable is an unwanted variable with a known relationship that influences the results.

Sampling Methods

• Random sampling ensures every population member has an equal chance of selection.
• Stratified sampling divides the population into strata and samples each proportionally.
• Non-random (convenience) sampling selects readily available participants without aiming for representativeness.

Data Types

• Quantitative data is numerical.
• Qualitative data is descriptive.
• Objective data comes from standard measurements.
• Subjective data is based on individual opinions.
• Primary data is collected directly by the researcher.
• Secondary data is collected by someone other than the original researcher.

Repeatability and Reproducibility

• Repeatability is the extent to which identical measurements or studies produce the same results.
• Reproducibility is the extent to which measurements or studies produce the same results under different conditions..

Conclusions and Implications

• With high internal validity, conclusions about the cause-effect relationship between tested variables can be drawn.
• A conclusion cannot be drawn if the study lacks internal validity.
• Implications arise when the hypothesis is supported.
• Implications prompt consideration of how results apply beyond the current study’s scope.

Validity

• Validity refers to the extent to which an assessment tool measures what it is designed to measure.
• Internal validity relates to how well the study was conducted and is impacted by extraneous/confounding variables.
• External validity relates to the applicability of findings beyond the study, and is impacted by sample size and representativeness.

Study Types

• Controlled experiments manipulate an IV to observe its effect on the DV while controlling other variables.
• Correlational studies observe and measure relationships between variables without manipulation.
• A case study is an in-depth analysis of an individual, group, or phenomenon.

Generalisation

• With high internal and external validity, a generalization can be made to the wider population of research interest.
• Generalisations require a representative sample and controlled extraneous variables.

Descriptive Statistics

• Used for analyzing, organizing, and summarizing data and can suggest relationships between variables.
• Mean is the average of scores.
• Median is the middle number in a dataset.
• Mode is the most frequent number.
• Standard deviation measures the spread of scores around the mean.

Ethical Considerations

• Informed consent requires providing participants with sufficient study information before they agree to participate.
• Voluntary participation means participants can refuse to take part in the study.
• Withdrawal rights allow participants to leave at any time and withdraw their results after completion.
• Confidentiality ensures participants are not identified in any way.
• Deception is only allowed if prior knowledge would confound the results.
• Debriefing involves informing participants about the study’s results, conclusions, and any deception used, after the study.

Study Designs

• Between-subjects design allocates participants to either the control or experimental condition.
• Within-subjects design exposes each participant to both the experimental and control conditions.
• Mixed design combines elements of within-subjects and between-subjects designs.