Study Notes on Research Population and Sampling

RESEARCH POPULATION AND SAMPLING

Definition of Key Concepts

• Population
    - Definition: A set of elements that the research focuses on and to which the obtained results should be generalized.
    - Source: (Bless and Higson-Smith, 2000: 85)

• Sampling
    - Definition: A process of selecting individuals from the population for a particular study.
    - Source: (Fraenkel and Wallen, 2003: 96)

Population and Sampling Relation

• The relationship between the population and sample entails selecting a sample from the population to generalize conclusions from the sample back to the population.

MAJOR TYPES OF SAMPLING

Categories of Sampling

• Probability Sampling
    - Definition: A type of sampling in which every element in the population has an equal chance of being selected.

• Non-Probability Sampling
    - Definition: Non-random procedures for selecting the members of the sample.

TYPES OF PROBABILITY SAMPLING

Different Approaches to Probability Sampling

1. Simple Random Sampling
      - Definition: Every member of the population has an equal and independent chance of being included in the random sample.

2. Stratified Sampling
      - Definition: A sample that consists of a number of subgroups, or strata, selected to represent the population.
      - Important for ensuring that specific characteristics are proportionate.

3. Cluster Sampling
      - Definition: Selecting a sample that is alike with respect to characteristics relevant to the variables of the study.
      - Involves dividing the population into clusters and randomly selecting clusters for study.

4. Systematic Sampling
      - Definition: Drawing a sample by taking every 10th case from a list of the population.
      - Requires a list of the population in advance.

TYPES OF NON-PROBABILITY SAMPLING

Different Approaches to Non-Probability Sampling

1. Convenient Sampling
      - Definition: Selecting the first available individuals encountered.
      - Often used for its practicality, but may introduce bias.

2. Purposive/Judgemental Sampling
      - Definition: Sampling elements judged to be typical or representative of the population.
      - Relies on the researcher’s discretion to select specific individuals based on predefined criteria.

3. Quota Sampling
      - Definition: Selecting typical cases from diverse strata of a population to meet a preset quota.
      - Ensures representation from various sectors of the population.

VARIABLES IN RESEARCH

Definitions and Examples

• Independent Variable
    - Definition: The variable that is manipulated, controlled, or changed in an experiment or study.
    - Example: A teacher using reinforcement techniques to encourage student performance.

• Dependent Variable
    - Definition: The variable that changes as a result of manipulation of the independent variable.
    - Example: The change in student performance resulting from the teacher's reinforcement.

DATA COLLECTION STRATEGIES

Quantitative Data Collection Methods

• Questionnaires
    - Description: Can be administered personally or mailed out.
    - Survey Questionnaires
    - Application: Often used in field market research.

Qualitative Data Collection Methods

• Observations
    - Description: Use of field notes or recordings to document behaviors or events.

• Interviews
    - Description: Can involve individuals or focus groups, including telephonic interviews.

• Documents
    - Types: Public documents such as newspapers, reports, and articles that provide relevant information for analysis.

• Audio-Visual Materials
    - Types: Photographs and objects that can provide visual context to the research.

SELF-ASSESSMENT ACTIVITY

Task Instructions

• Use a table format to provide advantages and disadvantages of using quantitative and qualitative research approaches.
    - Objective: To critically assess the strengths and weaknesses of both research methodologies in context to your study objectives.