Quantitative data collection methods are used to gather information from measurable sources. Data collected using quantitative methods tend to be viewed as yielding more accurate and objective information because the collection methods are standardized and can be replicated (NSF, 2002). Examples of quantitative data collection methods include quantitative surveys, structured interviews, and quantitative observation. Once data is collected using these methods, it is presented as statistics. Statistics make it easier to interpret large amounts of data. Unlike qualitative data collection methods, quantitative data collection often makes use of large sample sizes to analyze a group of people or an environment.
Quantitative surveys differ from qualitative surveys in that they use questionnaires with closed-ended, multiple-choice questions. Quantitative surveys are ideal when surveying large groups of respondents. The standardized nature of the questionnaires allows researchers to generalize from the results. While quantitative surveys may seem more precise than qualitative surveys, that is not always the case. Limited response options and over-generalizations often make quantitative survey results less accurate than qualitative survey results. However, HR departments still prefer to use quantitative survey questions when they need to report organizational trends more efficiently at a high level. For example, the C-suite (executive-level managers) may want HR to report the information using charts and graphs that require numeric data points in order to be produced.
One-on-one interviews can also be conducted to gather quantitative data. These interviews are more structured than those used to collect qualitative data, and they involve limited answer choices. Quantitative interviews can be conducted face-to-face, via telephone, or via the internet. They may be conducted by humans or AI.
Quantitative observation involves collecting observable data that can be measured and expressed numerically. While the data is collected from the perspective of the individual doing the collecting, the output should be expressed in objective terms. This objectivity is possible, at least in part, by ensuring that the data is collected and reported in a systematic way. Objectivity is also achieved by measuring the collected data in a standardized way.