Samples Surveys Observations

Research Methodology Overview

Introduction to Sampling in Research

• Importance of obtaining volunteers for research studies.

• Population: A complete set of observations, events, or individuals sharing common characteristics relevant to the research. Examples include plants, animals, and different demographics (e.g., psychology students, children).

• Sample: A subset of the population used for research due to practical limitations associated with studying the entire population.

Types of Samples

1. Random Sampling

• Definition: Every individual in the population has an equal chance of being selected.

• Note: Most experiments struggle to achieve true random sampling despite its ideal nature.

2. Stratified Sampling

• Definition: Involves subdividing the population into established subsets and ensuring equal representation from each subset.

  • Example: Sampling an equal number of males and females to ensure balanced representation.

3. Cluster Sampling

• Definition: Involves randomly selecting entire groups rather than individuals.

  • Example: Choosing a whole sports team to represent its members collectively.

4. Accidental/Haphazard (Convenience) Sampling

• Definition: Non-scientific sampling often used for quick data collection.

  • Example: Mall questionnaires that may introduce bias due to non-representative samples.

Bias in Samples

• A biased sample systematically differs from the population it represents.

Explanations for Bias

1. Selection Bias: Flaws in the sampling method leading to over- or under-representation of certain population segments.

2. Response Bias: Distortions in sample representativeness due to non-responses from selected individuals.

3. Sampling Error: Variations between population mean and sample mean, which can occur even in unbiased samples.

Non-Experimental Research Methods

Surveys/Questionnaires

• Purpose: To assess people's attitudes, opinions, characteristics, or perceptions through written or oral formats.

Steps for Conducting Survey Research

1. Knowledge Base

   • Importance of familiarity with the research subject to create effective surveys.

2. Drafting Questions

   • Consideration of question quantity and relevance.

   • Avoid broad topics in a single survey.

3. Question Formats

   • Open-ended Questions: Allow for responses in respondents' own words (e.g., essay or short answer).

   • Closed-ended Questions: Present options which respondents select from (e.g., multiple choice, rating scales).

   • Partially Open-ended Questions: Combination of closed and open formats, allowing an 'other' write-in option.

4. Evaluating Questions

   • Avoid double-barreled questions (asking two questions at once).

   • Prevent negative wording and double negatives for clarity.

   • Ensure questions are not biased or leading the respondent.

5. Pretesting

   • Conduct a pilot study to identify potential issues with survey questions before actual data collection.

6. Finalizing Survey

   • Write final draft and distribute with clear instructions.

Anti-Bias Focus in Course Evaluations

• Statement on perceived instructor biases affecting feedback quality and urging students to consider biases when providing evaluations.

Observational Research Methods

Description

• Observational methods involve unobtrusive recording and description of behavior in natural settings, aiming to understand social interactions without pre-formulated hypotheses.

Types of Observations

1. Naturalistic Observations

   • Definition: Observing subjects in their natural environments, aiming for detailed documentation.

   • Challenges include environmental complexity and observer intrusiveness.

2. Structured/Controlled/Laboratory Observations

   • Definition: Researchers create controlled environments while attempting to simulate natural settings.

   • Potential pitfalls include the risk of behavior not reflecting true actions due to artificial conditions.

   • Concept of interobserver reliability: Agreement among multiple observers enhances the validity of observations.

Conclusion

• Emphasis on consistent operational definitions is crucial for enhancing reliability and validity in observational research.