Quantitative research involves collecting and analyzing numerical data to find patterns, averages, predictions, and cause-and-effect relationships among variables. This type of research is widely used in both the natural and social sciences (e.g., chemistry and psychology). Quantitative research might, for example, ask “What’s the relationship between job satisfaction and salary among New York City residents?” or “How much has the average temperature changed globally over the past five years?”, and the results can be used to establish behaviors or phenomena that can be generalized across populations.
Though similar in name, qualitative research collects and analyzes nonnumerical data (e.g., texts or videos) to find underlying meanings or relationship patterns or to understand concepts, thoughts, or experiences. The results aren’t generalizable; specific phenomena are studied in depth, and the findings and themes are specific only to the group studied (e.g., what it’s like to grow up in a single-parent family in a rural environment). Therefore, qualitative research can be done through observations or interviews with open-ended questions.
Quantitative Research Methods
Since quantitative research collects numerical data, such as statistics and percentages, so that they can be clearly expressed in numbers and charts, it must be done objectively and produce measurable results.
Here are a few examples of quantitative research methods:
● Surveys or questionnaires using closed-ended questions (e.g., multiple choice) or rating scales (e.g., the Likert scale) can produce results that can be translated numerically. Operationalization can be used for more abstract concepts.
● Observations of an identified behavior in its natural environment can be made as long as they’re systematic (i.e., unbiased and repeatable).
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Since quantitative research produces data that are statistically analyzed, it’s considered objective, rational, and unbiased, which allows for the results to be applied to other cultures, times, populations, etc.
Quantitative research also produces data that can be standardized (i.e., putting different variables on the same scale to allow comparison), which means that your results can be researched, analyzed, used, and reproduced by others. While this also allows for your results to be generalized across populations, they can also be used to test or confirm theories that have already been established.
The development of sophisticated software means data analysis can be done much faster and with huge amounts of data, so the speed and efficiency of the quantitative approach is very appealing to researchers.
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