Quantitative Research Overview

Questions and Answers

An experimental approach focused solely on qualitative data.

A subjective inquiry that gathers in-depth insights through interviews.

Research primarily based on literature and theoretical frameworks.

Research that relies on numerical data and statistical analysis. (correct)

Focuses on deriving new theories from collected data. (correct)

Utilizes structured tools like surveys for data collection.

Seeks to measure variables and identify relationships.

Employs statistical methods for data analysis.

Allows for generalization of findings across larger populations. (correct)

Enables subjective interpretation of data outcomes.

Relying on flexible methodologies to guide research design.

Provides in-depth understanding of individual experiences.

<p>It often fails to capture the richness of human experience.</p> Signup and view all the answers

<p>The use of non-standardized measurement instruments.</p> Signup and view all the answers

Study Notes

Quantitative research involves systematic investigation that primarily focuses on quantifying relationships, behaviors, or phenomena, often utilizing statistical methods for analysis.

Employs structured data collection tools such as surveys, questionnaires, and experiments to gather numerical data.
Data is analyzed using statistical techniques, allowing for objective assessment of variables and relationships.
Typically includes large sample sizes to enhance the reliability and generalizability of results.
Aims for replicability, ensuring that studies can be repeated with similar results under the same conditions.
Findings are presented through graphs, tables, and charts to facilitate easy interpretation and visualization.

Strengths include the ability to produce reliable data that can be generalized across larger populations, providing a strong basis for causal inference.
The structured nature of quantitative research allows for high levels of precision and objective measurement of variables.
Weaknesses involve potential oversimplification of complex human behaviors or social phenomena, which may not be fully captured by numerical data.
Contextual factors may be overlooked, limiting understanding of underlying motivations and perspectives influencing the data.
Researchers may face challenges in ensuring data validity and reliability, particularly if sampling methods are flawed or not representative.