Characteristics, Strengths, Weakness, and Kinds of Quantitative Research |SHS| Practical Research 2

Research is not merely gathering information, rummaging for hard-to-find facts, or simply collecting and transporting facts from one location to another. True research involves interpretation, analysis, and a systematic approach to understanding phenomena.

Research is a systematic process of collecting, analyzing, and interpreting information or data to increase understanding of a phenomenon. It is methodical and follows a research process to achieve accurate results. Research is also iterative, meaning researchers may need to move back and forth between steps, and it is a continuous cycle that often begets more research rather than providing total closure to a problem.

Qualitative research requires non-numerical data and uses words, while quantitative research involves the measurement of numerical data. Qualitative research is exploratory and generates hypotheses, often working with small samples. Quantitative research is conclusive, tests hypotheses, and typically uses large, randomly sampled groups to achieve generalizable data. Qualitative data generally uses open-ended questions, while quantitative data uses closed-ended questions.

Quantitative research is objective, meaning data gathering and analysis are done accurately and are unaffected by personal bias. It has a large sample size to obtain meaningful statistical results and is generalizable and reliable when conducted with sufficient sample size and random sampling. Data collection can be quick and easy using standardized instruments, and data analysis is faster using statistical tools. Results are visually presentable through graphs, charts, and tables, and quantitative research is replicable to validate findings and ensure generalizability.

Numerical and quantifiable data can be used to predict outcomes. It offers fast and easy data analysis using statistical software, is objective, and benefits from the validity and reliability of survey questionnaires.

Quantitative research lacks the necessary data to explore problems or concepts in depth and does not provide comprehensive explanations of human experiences. Some information, such as feelings and emotions, cannot be described by numerical data. Additionally, a large sample size can make data collection more costly.

Non-experimental designs include descriptive, correlational, and ex-post facto (causal-comparative) research. Descriptive research describes a phenomenon by observing it as it occurs naturally without manipulation or initial hypothesis (e.g., number of hours spent on social media). Correlational research identifies relationships between variables without implying cause and effect. Ex-post facto research investigates causal relationships between existing conditions, where the independent variable is not manipulated but identified from past events (e.g., attitudes of academic vs. TVL students towards practical research).

Quasi-experimental research establishes cause and effect between variables but has lesser validity due to the absence of random selection and assignment of participants, using naturally occurring groups. Experimental research is the most rigorous, establishing cause-and-effect relationships through manipulation of an independent variable and random assignment of participants to experimental and control groups.