Types of Research Designs

Study Notes

Qualitative Research: Focuses on exploring attitudes, behaviors, and opinions through non-numerical data (e.g., texts, images, observations).
Quantitative Research: Focuses on testing hypotheses and predicting outcomes through numerical data (e.g., surveys, experiments).
Mixed-Methods Research: Combines qualitative and quantitative approaches to provide a more comprehensive understanding.

Experimental Design: Involves manipulating an independent variable to observe its effect on a dependent variable.
Quasi-Experimental Design: Lacks random assignment of participants, but still attempts to establish cause-and-effect relationships.
Survey Design: Involves collecting data through self-report measures (e.g., questionnaires, interviews).
Case Study Design: In-depth examination of a single case or a small number of cases.
Content Analysis Design: Analyzes and interprets text, images, or other media.

Probability Sampling: Every member of the population has an equal chance of being selected (e.g., random sampling, stratified sampling).
Non-Probability Sampling: Selection is based on convenience, expertise, or other factors (e.g., purposive sampling, snowball sampling).

Primary Data: Collected firsthand through experiments, surveys, or observations.
Secondary Data: Collected from existing sources (e.g., literature reviews, databases).

Descriptive Statistics: Summarizes and describes the basic features of the data.
Inferential Statistics: Makes inferences about the population based on the sample data.
Qualitative Data Analysis: Identifies patterns, themes, and codes in non-numerical data.

Informed Consent: Participants must be aware of the risks, benefits, and procedures involved.
Confidentiality: Protecting participants' identities and data.
Anonymity: Ensuring participants' identities are not revealed.
Deception: Avoiding misleading or deceiving participants.

Internal Validity: Ensuring the study's design and procedures are sound.
External Validity: Ensuring the results can be generalized to other populations and settings.
Reliability: Ensuring the consistency and accuracy of the measurements.

Qualitative Research: Explores attitudes, behaviors, and opinions through non-numerical data like texts, images, and observations.
Quantitative Research: Tests hypotheses and predicts outcomes through numerical data from surveys, experiments, and other methods.
Mixed-Methods Research: Combines qualitative and quantitative approaches to provide a comprehensive understanding.

Experimental Design: Manipulates an independent variable to observe its effect on a dependent variable.
Quasi-Experimental Design: Lacks random assignment of participants but still attempts to establish cause-and-effect relationships.
Survey Design: Collects data through self-report measures like questionnaires and interviews.
Case Study Design: Involves an in-depth examination of a single case or a small number of cases.
Content Analysis Design: Analyzes and interprets text, images, or other media.

Probability Sampling: Every member of the population has an equal chance of being selected.
Non-Probability Sampling: Selection is based on convenience, expertise, or other factors.

Primary Data: Collected firsthand through experiments, surveys, or observations.
Secondary Data: Collected from existing sources like literature reviews and databases.

Descriptive Statistics: Summarizes and describes the basic features of the data.
Inferential Statistics: Makes inferences about the population based on the sample data.
Qualitative Data Analysis: Identifies patterns, themes, and codes in non-numerical data.

Informed Consent: Ensures participants are aware of risks, benefits, and procedures involved.
Confidentiality: Protects participants' identities and data.
Anonymity: Ensures participants' identities are not revealed.
Deception: Avoids misleading or deceiving participants.

Internal Validity: Ensures the study's design and procedures are sound.
External Validity: Ensures the results can be generalized to other populations and settings.
Reliability: Ensures the consistency and accuracy of the measurements.