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Psychology may bring to mind images of psychoanalysis and dream interpretation, but many professional psychologists prefer more empirical approaches to studying human behavior. Such professionals conduct research by designing experiments that gather numerical, quantitative, data. Researchers in quantitative methods psychology can then use statistical analysis of their experiment's data to draw conclusions about its results.
All researchers gather and analyze data. This information can can be quantitative or qualitative in nature. Qualitative data can include interviews a psychologist may conduct with subjects, his or her notes when observing a subject's behavior, or case studies written by other researchers. Psychologists doing research with qualitative data will analyze the information from all these sources for connections and patterns, then write papers that state their findings, and present their arguments to justify their conclusions.
Other psychologists work with quantitative data. Using numbers allows them to run their data through equations and statistical models that can quantify the existence, and strength, of any patterns or relationships the researchers may find. Researchers that work in quantitative methods psychology prefer collecting and analyzing numerical data so that their conclusions can be mathematically proven, instead of relying on the arguments that qualitative researchers use to justify theirs. Some of these psychologists believe that working with quantitative methods makes the field of psychology more empirically rigorous and improves the quality of its academic research.
Quantitative methods psychology can collect data for analysis by examining things that are inherently numerical, or by using a system of coding to quantify items that are more qualitative in nature. Information that is inherently quantitative can include items such as the time it takes subjects to respond to a stimulus, or the number of subjects that select a particular answer to a question on a survey. Psychologists can also code types of behavior in subjects they are observing. This involves the researcher establishing broad definitions of the behaviors in which he or she is interested, and assigning a number to each one. Recording a number when the psychologists observe its corresponding behavior allows these researchers to create quantitative data from qualitative observations.
One of the most common analytical techniques in quantitative methods psychology is regression analysis. The researcher divides his or her data into an independent data series and a dependent data series. When this data is run through a linear regression model, the psychologist gets a set of numbers that describe the extent to which the independent data series affects the dependent data series. If the researcher was studying the effect of a day's temperature on behavior, then the temperature would the independent variable and the code for the behavior would be the dependent variable. Psychologists using this quantitative technique would use the results of the regression analysis to determine the strength and validity of the independent variable's affect on the dependent variable.
Regression analysis is popular in quantitative methods psychology because of its ability to determine causation. Correlations can only tell if there is a relationship between two data series, not which data series is causing changes in the other. For example, a strong correlation between temperature and behavior cannot mathematically prove that the temperature is what is causing the behavior. Regression analysis can mathematically prove that the independent variable is what is affecting the dependent variable, which allows researchers to use its results as evidence.
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