Quantitative Research Essentials

Research Methods Overview

  • Two broad approaches: quantitative vs. qualitative
  • Choice driven by: research questions, philosophical stance, personal skills/preferences

Basic Principles of Research Design

  • Ontology: researcher’s view of reality (e.g., "Are feelings real?")
  • Epistemology: beliefs about the best way to investigate reality (e.g., moral justification of lying)
  • Methodology: coherent grouping of techniques
  • Methods & techniques: concrete tools for data collection/analysis

Quantitative Data: Definition & Scope

  • Data expressed in numerical form; suitable for mathematical/statistical treatment
  • Widely used in economics, finance, natural sciences, psychology, sociology\text{economics},\,\text{finance},\,\text{natural\ sciences},\,\text{psychology},\,\text{sociology}

Key Characteristics of Quantitative Data

  • Numerical values (whole numbers, decimals, fractions)
  • Measures countable/ measurable variables (height, weight, income, etc.)
  • Continuous (any value in range) or discrete (distinct values)
  • Considered objective & reliable due to precise measurement

Main Types of Quantitative Data

  • Descriptive: summarizes phenomena (central tendency, dispersion)
  • Inferential: draws conclusions about populations (hypothesis tests, correlation, regression)
  • Time-series: observations across time; tracks trends/patterns
  • Cross-sectional: snapshot at one point in time

Data Collection Methods

  • Surveys/questionnaires: structured questions to a sample
  • Experiments: manipulate independent variables to test effects
  • Observational studies: measure phenomena without interference
  • Secondary data analysis: use existing datasets (government, academic, databases)

Data Analysis & Interpretation

  • Statistical analysis: summarize & test data using appropriate statistics
  • Data visualization: graphs & charts for readability
  • Interpretation: draw conclusions while acknowledging assumptions & limitations

Common Concerns for Quantitative Researchers

  • Adequacy of sample size nn
  • Selection of correct statistical tests
  • Minimizing Type II / Type IIII errors
  • Generalisability of findings
  • Reproducibility of methods/results
  • Validity of measurement instruments

Limitations of Quantitative Research

  • Not all phenomena are measurable or measured accurately
  • Limited insight into underlying "why"
  • Potentially impersonal—little direct engagement with participants
  • Often provides static snapshots
  • Numbers may persuade but can still misrepresent reality