Quantitative research, also known as empirical research, is the use of numbers for data analysis. Disciplines in which various types of quantitative research are used include science, epidemiology and medicine. Researchers can collect the numbers manually or automatically, depending on the kind of research and the required level of preciseness and accuracy.
Manual data collection is typically reliable for small data sets where the margin of error is minimal. Automated data collection, where the human error factor is removed, is generally regarded as the most accurate type of quantitative research.
Quantitative research involves gathering absolute data, such as numerical data, so that the manner in which it is examined is as unbiased as possible. Quantitative research usually comes later in a research project, at a stage when the scope of the project is well understood, and it is more closely aligned with what is considered the classical scientific paradigm. Quantitative research results in a collection of numbers, which can then be subject to statistical analysis in order to come to results. A key aspect of this type of research is for the researcher to remain separate from the research emotionally and to remove researcher bias.
Medicine also applies quantitative research in many ways. Some common quantitative parameters used in clinical research trials include cardiology, pathology and physical measurements. An automated data collection process is used to count the amount of white and red blood cells and electrolytes in blood levels.
In social sciences any research that makes inferences about the phenomenon it studies on the basis of numbers is quantitative research. Its hallmarks are control over extraneous influences and statistical approaches to measurement, sampling and data analysis.
Different types of quantitative research can be discussed using the goals of research. A descriptive research strategy is used when it is the numerical description of an object, event, or situation that attracts researchers' interest. When researchers are interested in the extent to which two or more variables tend to co-occur, they employ a relational research strategy. Interest in casual relations would prompt researchers to use an experimental research strategy.
A distinction can also be made between experimental and non-experimental quantitative research. The essential feature of experimental research is the manipulation of a variable, best explored by the random assignment of study participants, which the non-experimental research lacks. A common type of study in social sciences known as a quasi-experiment bridges these two types of quantitative research. The quasi-experiment has many of the features of an experiment but study participants are not assigned randomly as part of the study.
Quantitative research can also be divided into cross-sectional and longitudinal research. In cross-sectional research, participants are surveyed at one point in time, while longitudinal research involves participants at multiple points in time. Therefore, cross-sectional-research provides a snapshot of participants, while an analysis of change in participants over time is possible thanks to longitudinal research.
Qualitative research often results in narrative descriptions as opposed to the numerical and statistical form of quantitative research. Values produced by qualitative research are based on a scale or grade. While still being valuable, this type of data has less statistical power than that resulting from quantitative research. There have been many attempts to find a stronger synthesis between the two types of research in recent years, but many social scientists fall sharply on one side or the other and the debate is still continuing.