Practical Research 2: Nature of Inquiry

Introduction to Quantitative Research

• Research methods are classified into two main types: quantitative and qualitative; quantitative focuses on measurement and quantity.
• Quantitative research involves scientifically collected, statistically analyzed data to explore observable phenomena.
• Data must be numerical and quantifiable, allowing statistical analysis techniques such as Pearson's r, t-test, and Analysis of Variance (ANOVA).

Characteristics of Quantitative Research

• Large Sample Size: Ensures meaningful statistical results by gathering data from many subjects.
• Objectivity: Data gathering and analysis are conducted without researcher bias, relying on factual observation.
• Visual Result Presentation: Numerical data allows clear and effective visual representations.
• Faster Data Analysis: Utilization of statistical tools streamlines the process.
• Generalizable Data: Findings from a sample can apply to the larger population if proper sampling techniques are used.
• Fast Data Collection: Standardized instruments facilitate quick data acquisition from large samples.
• Reliable Data: Objective analysis fosters credibility for decision-making and policymaking.
• Replication: The research method can be repeated to confirm findings, enhancing validity.

Strengths of Quantitative Research

• Findings can be replicated to verify results.
• Research results are generalizable across populations.
• Establishes cause and effect relationships conclusively.
• Numerical data aids in predicting outcomes effectively.
• Enables rapid analysis with statistical software.
• Facilitates quick data gathering processes.
• Maintains objectivity in results.
• Validity and reliability are easily measurable.

Weaknesses of Quantitative Research

• May lack depth in exploring complex problems or experiences.
• Fails to provide comprehensive explanations of human behavior.
• Cannot capture nuanced information, such as emotions or beliefs, which aren't quantifiable.
• Research design tends to be rigid, limiting flexibility.
• Respondents often limited to fixed response options, potentially skewing data.
• Risk of respondents providing inaccurate or biased answers.

Types of Quantitative Research Designs

• Descriptive Design: Observes and describes phenomena without manipulation or hypothesis testing, e.g., studying physical activities of students during quarantine.
• Correlational Design: Examines relationships between variables based on observations, such as the link between physical activity and academic performance.
• Quasi-Experimental Design: Investigates cause-and-effect relationships with less validity due to no random selection; compares treatment and control groups, e.g., effects of unemployment on safety protocol adherence.
• Ex Post Facto Design: Analyzes relationships between past events and current conditions without manipulation, e.g., how parental academic success affects children’s obesity.
• Experimental Design: Employs random assignment to establish definitive cause-and-effect relationships, e.g., comparing antibiotic effectiveness on pneumonia treatment.

Experimental Design Features

• Involves manipulating an independent variable, e.g., medication.
• Participants are randomly assigned to treatment and control groups, enhancing reliability of results.
• Random assignment distinguishes effects attributable to the independent variable from those of confounding factors.