MEV 019: Unit 03 - Research Design
3.1 Introduction
A research design is the blueprint or strategic
framework for conducting research. It provides structure to the research
process, guiding the collection, measurement, and analysis of data. In
environmental science, well-constructed research design is crucial due to the
complexity, variability, and interdisciplinary nature of environmental
phenomena.
3.2 Objectives
After studying this unit, you will be able to:
- Understand the importance and functions of research design.
- Identify various types of research designs.
- Learn how to develop a research plan.
- Explain the role and types of sampling.
- Distinguish between probability and non-probability sampling
techniques.
3.3 Need for Research Design
Research design ensures that the evidence
collected enables the researcher to effectively address the research problem.
It helps:
- Avoid unnecessary data collection.
- Ensure accuracy and reliability of results.
- Provide a logical and systematic approach.
- Enhance efficiency and reduce bias.
In environmental studies, research design
allows integration of field data, laboratory analysis, and modeling tools.
3.4 Principles of Research
Design
Good research design follows these key
principles:
- Objectivity: Maintain neutrality in methods and interpretation.
- Reliability: Reproducibility of results under similar conditions.
- Validity: Ensure accurate measurement of concepts.
- Generalizability: Ability to apply
results to a larger population.
- Economy: Achieve goals using optimal resources.
3.5 Types of Research Designs
Depending on purpose and methodology, research
designs are categorized into:
- Exploratory Research Design: For new or unstudied
problems; flexible and open-ended.
- Descriptive Research Design: Describes
characteristics of a population or phenomenon.
- Diagnostic Research Design: Determines causes of a
condition or event.
- Experimental Research Design: Manipulates variables
to examine causal relationships.
Environmental Example:
- Descriptive: Survey of biodiversity in a forest region.
- Experimental: Testing pollutant impact on plant growth in controlled settings.
3.6 Developing a Research Plan
– Exploration, Description, Diagnosis and Experimentation
Developing a research plan includes the
following phases:
- Exploration: Initial study to identify issues, trends, or ideas.
- Description: Collection of data to describe conditions or relationships.
- Diagnosis: Identification of causes and their effects.
- Experimentation: Hypothesis testing by controlling variables.
Each stage refines the focus and enhances
understanding of the research topic.
3.7 Sampling Techniques
Sampling involves selecting a subset of
individuals, items, or observations from a larger population to draw
conclusions.
Why Sampling?
- More practical than studying the entire population.
- Saves time, money, and effort.
- Essential for statistical analysis.
Environmental research often uses sampling to
assess soil quality, water pollution, or population dynamics.
3.8 Need for Sampling
- Cost-effectiveness: Whole-population studies
are expensive and time-consuming.
- Feasibility: Sampling is suitable when complete data collection is not
possible.
- Timeliness: Enables quicker decision-making based on representative data.
3.9 Significant Terms in
Sampling
- Population: Total group of interest.
- Sample: Subset drawn from the population.
- Sampling Frame: List from which sample is drawn.
- Sampling Unit: Individual element considered for selection.
- Sampling Error: Difference between sample estimate and actual population value.
3.10 Types of Sampling Designs
Sampling designs are broadly classified into
two categories:
- Probability Sampling: Every member has a
known, non-zero chance of selection.
- Non-Probability Sampling: Some elements have no
chance or unknown chance of being selected.
3.11 Probability Sampling
Procedures
- Simple Random Sampling: Every unit has equal
chance of selection.
- Systematic Sampling: Every nth unit is
selected from a list.
- Stratified Sampling: Population divided into
strata; random samples taken from each.
- Cluster Sampling: Population divided into
clusters, some clusters are randomly selected.
Example:
For river water quality: Stratify by seasons (monsoon, summer, winter), then
randomly sample locations within each season.
3.12 Non-Probability Sampling
Procedures
- Convenience Sampling: Select the most
accessible units.
- Judgmental (Purposive) Sampling: Select based on expert
judgment.
- Quota Sampling: Ensure certain characteristics are represented in desired
proportions.
- Snowball Sampling: Existing subjects refer
new participants (common in community-based environmental studies).
Use Case:
Snowball sampling is useful in tracking illegal wildlife trade networks or
endangered species sightings.
3.13 Let Us Sum Up
Research design is a critical component of
scientific inquiry. This unit explored the significance of design in
structuring research, highlighted various research types, and explained the
steps in developing a research plan. We also examined the concepts and types of
sampling, helping researchers gather representative and reliable data essential
for valid environmental studies.
3.14 Key Words
- Research Design: Blueprint for conducting research.
- Exploratory Study: Initial investigation
of a topic.
- Descriptive Study: Describes
characteristics without establishing causality.
- Sampling: Selection of a subset from a population.
- Probability Sampling: Sampling with known
chances of selection.
- Non-Probability Sampling: Selection not based on
chance.
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