Research Design Notes

Research Method

  • Procedure or technique to undertake research.
  • Explains data identification, collection, processing, and analysis.
  • Provides scientific steps for solving research problems.

Research Methodology

  • Systematic, theoretical analysis of research methods.
  • Theoretical framework supporting chosen methods.
  • Science of systematically answering a research question; refers to the entire research process.
  • Includes research approach (qualitative, quantitative, mixed methods), methods (interviews, observation), and techniques (audio recordings, measurement scales).

Research Method vs. Research Methodology

  • Research Method: Techniques and procedures for solving research problems; narrower scope.
  • Research Methodology: Study of research methods to justify method preference; broader scope.

Research Design

  • Framework or plan for a study, guiding data collection and analysis.
  • Blueprint for collection, measurement, and analysis of data.
  • Master plan specifying methods and procedures for data collection and analysis (William Zikmund).

Key Design Decisions

  • What is the study about?
  • Why is the study being made?
  • Where will the study be carried out?
  • What type of data is required?
  • Where can the required data be found?
  • What periods of time will the study include?
  • What will be the sample design?
  • What techniques of data collection will be used?
  • How will the data be analyzed?
  • In what style will the report be prepared?

Characteristics of Good Research Design

  • Freedom from Bias: Data collection and analysis should not systematically vary the data.
  • Freedom from Confusing: Variables should be separated to avoid influencing each other.
  • Within Resources: Study should be completed within available time, money, and staff.
  • Objectivity: Consistent results regardless of the researcher.
  • Flexibility: Ability to deviate from the design due to real-world problems.
  • Statistical Precision: Data recorded at a level that yields statistically meaningful results.

Purpose of a Research Design

  • Minimize expenditure of effort, money, and time.
  • Facilitate smooth scaling of research operations.
  • Collect relevant data and techniques.
  • Provide a blueprint for plans.
  • Provide direction to executives and helpers.

Importance of Research Design

  • States what is to be done to achieve research objectives and how.
  • Furnishes minimum information for planning.
  • Provides a clear idea of activities needed to achieve the research objective.
  • Helps in providing direction to the computation and interpretation process.

Research Design Types

  • Quantitative: Experimental (True, Quasi, Pre) and Non-Experimental (Descriptive, Developmental, Surveys, Cause-comparative, Predictive, Relationship).
  • Qualitative: Historical, Phenomenological, Ethnographic, Case Study, Grounded Theory.

Quantitative Research

  • Collection and evaluation of numerical data to test a hypothesis or identify patterns.
  • Aims to quantify variables and measure their effects.
  • Gathers numerical data through surveys or experiments, analyzed using statistical techniques.

Types of Quantitative Research

  • Descriptive: Understand a phenomenon, situation, or population; identifies characteristics, categories, and trends using case studies, observations, and surveys.
    • Advantages: Detailed understanding, easy implementation, generalizable findings.
  • Survey: Gathers data through questionnaires from a wide population; can be cross-sectional (one point in time) or longitudinal (various durations).
    • Advantages: Wide audience reach, versatile, standardized data, anonymity.
  • Correlational: Identifies relationships between two variables without extraneous influence.
    • Advantages: Establishes relationships without manipulation, predicts outcomes, ethical alternative when manipulation is unethical, cost-effective using existing data.
    • Positive correlation: variables change in the same direction.
    • Negative correlation: variables change in opposite directions.
    • Zero correlation: no relationship.
  • Quasi-Experimental: Identifies cause-and-effect relationships but with non-random group assignments.
    • Advantages: Compares groups/conditions, high ecological validity (real-world settings), practical and feasible.
  • Experimental: Measures the effect of independent variables (IVs) on dependent variables (DVs) using the scientific method with random subject assignment.
    • Advantages: High internal validity, replication and verification of outcomes, manipulation of independent variables.

Basic Principles of Experimental Designs

  • Principle of Replication: Repeat experiment more than once to increase statistical accuracy.
  • Principle of Randomization: Protect against extraneous factors by randomization.
  • Principle of Local Control: Vary known sources of variability deliberately to measure & eliminate from error.

Qualitative Research Design

  • Focuses on exploring and understanding complex phenomena and meanings attributed by individuals or groups

Key Characteristics of Qualitative Research Design

  • Exploratory nature
  • Emphasizes on contextual understanding
  • Subjectivity and reflexivity
  • Small and purposive sampling
  • In-depth data collection
  • Iterative data analysis

Phenomenological Research

  • Focuses on audience experiences and recording/analyzing their beliefs, feelings and perceptions

Ethnographic Research

  • Ethnographic research is a qualitative research method involving the systematic study of people in their natural environment to understand their way of life, including how they see and interact with the world around them

Grounded Theory

  • Develop theories grounded in data through constant comparison and analysis, identifying categories, concepts, and relationships.

Sampling

  • The process of drawing a subset of people from a population so that results with that subset may be generalized to the population.

Significance of Sampling

  • Saves money and time.
  • May be more accurate than a census.

Types of Sampling Design

  • Probability sampling
  • Non-probability sampling

Non-probability Sampling

  • Convenience sampling
  • Voluntary response sampling
  • Purposive sampling
  • Snowball sampling

Probability Sampling

  • Simple random sampling
  • Systematic sampling
  • Cluster sampling

Sampling Error

  • A sampling error is a statistical error that occurs when an analyst does not select a sample that represents the entire population of data and the results found in the sample do not represent the results that would be obtained from the entire population.

Sources of Data

  • Primary Data: collected by a researcher from first- hand sources, using methods like surveys, interviews, or experiments.
  • Secondary data: data that are already available i.e., they refer to the data which have already been collected and analysed by someone else.

Reliability and Validity in Research

  • Reliability refers to how consistently a method measures something. If the same result can be consistently achieved by using the same methods under the same circumstances, the measurement is considered reliable.
  • Validity refers to how accurately a method measures what it is intended to measure. If research has high validity, that means it produces results that correspond to real properties, characteristics, and variations in the physical or social world.