Outline the features of research design.

1. Purpose: The research design should clearly outline the purpose of the study, including the research questions or hypotheses that will be addressed.

2. Research approach: The design should specify the overall approach that will be used to conduct the study, such as qualitative, quantitative, or mixed methods.

3. Sampling strategy: The design should detail how participants will be selected for the study, including the criteria for inclusion and exclusion.

4. Data collection methods: The design should outline the methods that will be used to collect data, such as surveys, interviews, observations, or experiments.

5. Data analysis: The design should describe how the collected data will be analyzed, including the specific statistical or qualitative techniques that will be used.

6. Time frame: The design should include a timeline for the study, outlining when data will be collected, analyzed, and reported.

7. Ethical considerations: The design should address any ethical considerations related to the study, such as informed consent, confidentiality, and potential risks to participants.

8. Validity and reliability: The design should outline how the study will ensure the validity and reliability of the findings, such as through the use of standardized measures or multiple data sources.

9. Budget and resources: The design should specify the resources needed to conduct the study, including funding, personnel, and equipment.

10. Limitations: The design should acknowledge any limitations of the study, such as sample size, generalizability, or potential biases, and discuss how these limitations will be addressed.

Research Design Features

1. Purpose:
- Explanatory: To identify causal relationships
- Descriptive: To document and describe phenomena
- Exploratory: To gather preliminary information and insights

2. Sampling:
- Random: Selects participants or data points randomly
- Non-random: Selects participants or data points based on specific criteria
- Sample size: Determines the number of participants or data points needed for statistical significance

3. Data Collection:
- Quantitative: Uses numerical data to measure and analyze variables
- Qualitative: Uses non-numerical data (e.g., interviews, observations) to explore and understand phenomena
- Mixed methods: Combines quantitative and qualitative methods for a more comprehensive approach

4. Variables:
- Independent variable: The variable that is manipulated or changed to examine its effect
- Dependent variable: The variable that is observed and measured to determine the effects of the independent variable
- Control variables: Variables that are held constant to minimize their impact on the results

5. Experimental and Quasi-Experimental Designs:
- Experimental design: Involves manipulating the independent variable to establish a causal relationship
- Quasi-experimental design: Allows for non-randomized assignment of participants or data points, but still seeks to control for confounding variables

6. Non-Experimental Designs:
- Observational design: Observes and records data without manipulating variables
- Correlational design: Examines the relationship between two or more variables without establishing causation
- Case study design: Focuses on in-depth exploration of a single case or group

7. Data Analysis:
- Statistical analysis: Uses statistical techniques to test hypotheses, analyze data, and draw conclusions
- Qualitative analysis: Interprets and analyzes qualitative data to identify themes, patterns, and insights

8. Ethical Considerations:
- Informed consent: Participants must be fully informed about the research and their rights
- Confidentiality: Participant data should be kept confidential
- Protection from harm: Participants should not be exposed to any physical or psychological harm