Research Chapter 2: Nature and Inquiry

Study Notes

Quantitative research utilizes scientifically collected and statistically analyzed data to study observable phenomena.
Focuses on facts or situations that need deeper understanding or exploration.

Employs scientific methods to design studies and collect numerical data.
Data must be numerical and quantifiable to allow for effective statistical analysis.

Numerical data is easier to collect compared to qualitative descriptions.
Examples of numerical data include:
- Student grades across subjects.
- Hours of social media engagement among teenagers.
- Consumer preferences for product packaging.
- Covid-19 patient recovery averages by region.

Non-numerical data can be transformed into numerical form using scales like the Likert scale.
Rating scales convert qualitative responses into quantifiable numerical data to facilitate mathematical operations.

Large Sample Size: Essential for achieving statistically significant results.
Objectivity: Data gathering and analysis remain unaffected by the researcher’s opinions.
Concise Visual Presentation: Numerical data allows for easy visualization through graphs, charts, and tables.
Faster Data Analysis: Statistical tools streamline the data interpretation process.
Generalized Data: Sample data can represent the larger population if collected appropriately.
Fast and Easy Data Collection: Standardized research instruments enable efficient data gathering from large samples.
Reliable Data: Data collected is seen as credible, aiding in informed decision-making.
High Replicability: Quantitative methods can be repeated to verify results, enhancing validity.