[ ] Nature of Inquiry [ ] Strengths and Weaknesses of Quantitative Research

Quantitative Research

Research Method: Classified into two main types: quantitative and qualitative. Quantitative is based on measurement or quantity, while qualitative involves understanding phenomena related to quality or kind.

Definition: Quantitative research uses scientifically collected and statistically analyzed data to investigate observable phenomena.

Phenomenon: Any existing or observable fact or situation we want to understand further.

Scientific Method: Involves designing and collecting numerical data, which undergo statistical analysis (e.g., Pearson's r, t-test, ANOVA).

Numerical Data: Easier to collect than descriptions in qualitative research. Examples include:

• Student's grades
• Social media engagement hours
• Consumer preferences
• Covid-19 patient recovery rates

Rating Scales: Used to quantify non-countable data. Example: Likert scale.

Characteristics of Quantitative Research

1. LARGE SAMPLE SIZE: Needed for meaningful statistical results.

2. OBJECTIVE: Data gathering and analysis are accurate and unaffected by personal biases.

3. VISUAL RESULT PRESENTATION: Data can be presented through graphs, charts, and tables.

4. FASTER DATA ANALYSIS: Statistical tools enable quicker analysis.

5. GENERALIZED DATA: Sample data can apply to the population if sampling is sufficient and random.

6. FAST DATA COLLECTION: Standardized instruments allow efficient data gathering from large samples.

7. RELIABLE DATA: Objectively analyzed data enhances credibility for decision-making.

8. REPLICATION: Quantitative methods can be repeated to verify findings.

Strengths of Quantitative Research

1. Can be replicated.

2. Findings are generalizable to the population.

3. Establishes cause and effect.

4. Numerical data predicts outcomes.

5. Fast data analysis with statistical software.

6. Fast data gathering.

7. Very objective.

8. Establishes validity and reliability.

Weaknesses of Quantitative Research

1. Lacks depth in exploring problems.

2. Does not explain human experiences comprehensively.

3. Some feelings and beliefs can't be quantified.

4. Rigid research design.

5. Limited response choices for participants.

6. Respondents may provide inaccurate responses.

7. Large sample sizes increase costs.

Kinds of Quantitative Research

Descriptive Design: Describes phenomena as they occur without manipulation or hypothesis. Example: "Determining the physical activities of high school students during quarantine."

Correlational Design: Identifies relationships between variables through observation. Example: "Relationship between physical activity and academic achievement."

Ex Post Facto Design: Investigates relationships between past events and present conditions without manipulation. Example: "How does parent's academic achievement affect child obesity?"

Quasi-Experimental Design: Establishes cause and effect with lesser validity due to non-random selection. Example: "Effects of unemployment on attitudes towards safety protocols."

Experimental Design: Establishes cause and effect with random assignment and manipulation. Example: "Effects of blended learning on reading comprehension."

Examples of Quantitative Research

• Effects of pandemic on social behavior and economic stability.
• Antidiabetic properties of common Philippine herbs.
• Effectiveness of organic vs. inorganic fertilizers on vegetable production.
• Diet and exercise techniques for various sports.
• Effectiveness of Facebook ads on sales.
• Effects of music on learning and behavior.
• Environmental factors affecting natural calamities.