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Objective: Not subjective; focuses on precision and accuracy.
- Emphasizes proof over discovery.
- Examples: Vaccine research for COVID-19.
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Clearly Defined Research Questions: Specific and precise.
- Research questions should clearly define respondents, interventions, comparison variables, and outcomes.
- Example: Research on COVID-19 vaccines should cover all aspects before the study begins.
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Structured Research Instruments: Well-planned and organized tools (questionnaires, checklists, etc.).
- Measure characteristics like age, gender, education, socioeconomic status, etc.
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Numerical Data Presentation: Data presented in numbers, statistics, tables, charts, graphs, and figures.
- Example: World Health Organization (WHO) charts and tables for COVID-19 data.
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Large Sample Size: More reliable data analysis with a larger sample size.
- Avoids biases; reflects normal population distribution.
- At least 20% of the population can be used as respondents.
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Replicable, Not Duplicable: Studies can be repeated to confirm results, not duplicated.
- Ensures validity and eliminates spurious conclusions.
- Example: Mix-and-match approach to COVID-19 vaccines.
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Predictive Data: Data can forecast future outcomes through mathematical calculations and computers.
- Uses past data to predict future trends.
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Verification and Development: Data can verify existing facts and develop new concepts.
- Research increases comfort in daily life.