Educational Research · Quick Revision

Research Methodology & Sampling

Representative sampling, statistical-test selection and sociometric mapping of classroom relationships.

Three Core Concepts

Concept 01

Probability vs. Non-Probability Sampling

Core principle/rule: Sampling reduces bias in educational studies. A sample is strictly representative only when selected through probability methods, where every individual has a known, non-zero chance of selection.

Probability Sampling · Random

  1. Simple Random: Every member has an equal chance—for example, drawing lots.
  2. Stratified Random: Divide the population into strata by a characteristic such as gender or grade, then randomly sample within each subgroup.
  3. Cluster Sampling: Randomly select intact groups—whole classrooms or schools—rather than individual students.

Non-Probability · Non-Random

  1. Purposive / Judgmental: Researcher handpicks subjects for expertise or relevance.
  2. Snowball Sampling: Existing subjects recruit others among acquaintances; useful for hard-to-reach groups such as high-school dropouts.
  3. Quota Sampling: Researcher fills predetermined subgroup quotas by convenience, without random selection.
Concept 02

Parametric vs. Non-Parametric Tests

Core principle/rule: The choice of statistical test depends strictly on the shape of the data distribution and its NOIR measurement scale.

Parametric Tests

Mathematically powerful; make strict assumptions about population parameters. Data must follow a Normal Distribution and use Interval or Ratio scales.

  • t-test: comparing means of two groups
  • ANOVA: comparing means of three or more groups
  • Pearson correlation

Non-Parametric Tests

“Distribution-free”; make no normality assumption. Used for heavily skewed data or Nominal or Ordinal scales.

  • Chi-Square: nominal frequency data
  • Mann–Whitney U: non-parametric alternative to t-test
  • Spearman Rank correlation: ordinal rankings
Concept 03 · Jacob Moreno

Sociometry

Core principle/rule: Sociometry is a highly specific quantitative method developed by Jacob L. Moreno to measure social dynamics, interpersonal relationships and peer acceptance within a defined group such as a classroom.

Key facts

  1. Mechanism: Ask students questions such as “Who are your three best friends in this class?” or “Who would you most like to work with on a project?”
  2. Sociogram: Plot the data as a visual map using nodes and arrows to show the network of choices and rejections.
StarReceives disproportionately many positive choices; highly popular.
IsolateNeither chosen nor rejected; simply flies under the radar.
RejecteeExplicitly receives negative choices or peer rejections.
CliqueClosed subgroup of three or more members who mutually choose one another and exclude outsiders.

Quick Reference

Table A · Parametric vs. Non-Parametric Framework

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FeatureParametric TestsNon-Parametric Tests
Data DistributionMust be Normal—Bell Curve.Distribution-free; can be skewed.
Measurement Scale RequiredInterval or Ratio data.Nominal or Ordinal data.
Comparing 2 GroupsIndependent t-testMann–Whitney U Test
Comparing 3+ GroupsANOVA—Analysis of VarianceKruskal–Wallis Test
Testing Categorical FrequenciesN/AChi-Square Test (χ²)

Table B · Sampling Method Quick-Check

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Goal of the ResearcherRequired Sampling TechniqueType
Ensuring every student has an equal chance.Simple RandomProbability
Ensuring exact proportional representation randomly.Stratified RandomProbability
Selecting whole classes instead of individuals.ClusterProbability
Finding hidden groups via referrals—for example, truants.SnowballNon-Probability
Selecting an expert panel of five senior teachers.Purposive / JudgmentalNon-Probability