Research methodology notes

Research: Systematic search for knowledge; careful investigation to discover new facts.
Need/Purpose:
- Expands knowledge, provides latest information.
- Identifies competition, builds credibility, narrows scope.
- Encourages problem-solving, reaches people, fosters curiosity.
Scope:
- Understanding competition, customer needs and product design.
- Maturing of management, stakeholder influence and global competition.
- Government intervention and economical data collection.
- Advantages: Helps identify opportunities, understand customers, minimize risks.
- Disadvantages: High costs, based on assumptions, time-consuming, potential for inaccurate info, quickly obsolete.

Descriptive vs. Analytical:
- Descriptive: Describes a phenomenon. Doesn't manipulate variables.
- Analytical: Analyzes data to find patterns, tests hypotheses.
Applied vs. Fundamental (Basic):
- Applied: Solves practical problems, improves existing products.
- Fundamental: Advances knowledge, explores new theories.
Quantitative vs. Qualitative:
- Quantitative: Numerical data, large samples, statistical analysis.
- Qualitative: Non-numerical data, small samples, in-depth analysis.
Conceptual vs. Empirical:
- Conceptual: Develops theories, abstract ideas.
- Empirical: Collects data to test hypotheses, real-world focus.
Other Types:
- Conclusion-oriented vs. Decision-oriented.
- One-time vs. Longitudinal.
- Field setting vs. Laboratory.

Literature Review: Summarizes previous research, theoretical base.
- Purpose: Knowledge foundation, identify gaps, justify research.
- Importance: Legitimacy, impact calculation, highlight contradictions.
- Steps: Select a topic, Search the literature, Develop the argument, Survey the literature, Critique the literature, Write the review
- Sources:
  - Primary Sources: Original materials. (e.g., Theses, scholarly articles).
  - Secondary Sources: Analysis/interpretation of primary sources. (e.g., Textbooks).
  - Tertiary Sources: Index/summarize other sources. (e.g., Encyclopedias).
Research Problem: Topic to study, address knowledge gap.
- Selection: Consider significance, originality, feasibility.
- Defining: Essential for relevant data, strategy planning.
- Techniques: Problem statement, understand nature, literature survey, discussions, rephrasing.
Research Design: Overall plan guiding the research process.
- Elements: Analysis method, methodology type, purpose statement.timeline.
- Nature: Systematic plan, methods used, procedures followed.
- Components: Objectives, questions, hypotheses, methodology, sampling.

Data: Facts/figures for research study and analysis.
Primary Data: Collected firsthand for a specific purpose.
- Methods: Observation, interviews, questionnaires, schedules, content analysis, projective techniques.
Secondary Data: Collected/compiled for other purposes.
- Sources:
  - Internal: Sales reports, financial statements.
  - External: Government censuses, business journals.
- Advantages: Time-saving, cost-effective, accuracy.
- Limitations: Lack of control, data quality, potential bias.
Primary vs. Secondary: Accuracy, control, relevancy, cost & time.
Sampling Techniques:
- Probability (Random) Sampling: all eligible individuals have a chance of being chosen for the sample
  - Simple random, systematic, stratified, cluster.
- Non-Probability (non-random) Sampling: some individuals have no chance of being selected.
  - Convenience, quota, judgment (purposive), snowball.

Data Processing: Transforming raw data into a useful format.
- Steps: Editing, coding, classifying, tabulating, diagrams.
- Stages: Collection, preparation, input, processing, output/interpretation, storage, report writing.
Types of Analysis:
- Text Analysis: Finding patterns in large datasets.
- Statistical Analysis: Using past data, Descriptive/Inferential Analysis.
- Diagnostic Analysis: Finding causes from statistical analysis.
- Predictive Analysis: Predicting future outcomes using past data.
- Prescriptive Analysis: Determining actions based on combined analysis.
Univariate Analysis: Explores each variable separately.
Bivariate Analysis: Investigates the relationship between two variables.
- Cross-tabulation: Connects two or more questions.
- Chi-Square Test: Determines difference between observed and expected data.
Hypothesis Testing: Determining evidence to support or refute a claim.
Statistical Packages:
- Sigma STAT/SPSS: Used for t-tests, ANOVA to identify correlations of data

Interpretation: Analyzing data to gain insights.
- Need: Transform raw data, identify patterns, clarify complex issues, guide decisions.
- Techniques: Descriptive statistics, graphical representation, comparative/correlation/regression analysis, hypothesis testing
Report Writing: Documenting research findings in a structured manner.
- Significance: Clear communication, record keeping, decision support.
- Components: Title, abstract, introduction, methodology, results, discussion, conclusion
- Report's purpose: Ensure transparency and accountability, facilitate data for understanding from different groups and departments.
- Precautions: Clarity, accuracy, objectivity, proper citation, and logical structure.
Types of Reports:
- Technical: For researchers, focuses on methods, assumptions.
- Popular: Simple, attractive, focuses on implications.
- Other Types: Survey, review, case study, market research, analytical, explanatory.