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measure of independent variables

In contrast to qualitative research, a quantitative study involves gathering information and attaching numerical values to each piece. Some types of information already have numbers attached to them (e.g., a person’s age in years), whereas other types are assigned numerical values by the researcher (e.g., the sex of an individual, where every male in a sample is coded as ‘‘0’’ and every female in the sample is coded as ‘‘1’’). When a researcher attaches his or her own numerical values, these values are determined by the researcher and must be defined for someone who is trying to understand the study. These scales or variables are then analyzed with statistics in order to make sense of the information for subsequent interpretation. Statistics, therefore, are also pieces of information, the difference being that the statistical information is a more general summary of the information gathered by a researcher. Numbers are assigned to pieces of information only when a researcher intends to apply statistics in order to produce new information that cannot be obtained through verbiage.

Unlike qualitative research, where a researcher remains ‘‘open’’ to new information, the types of information gathered from a quantitative study are determined before data collection begins. This is one reason why quantitative research is used primarily for theory/hypothesis testing, because such research involves collecting information that has already been described in a specifically worded hypothesis derived from a testable theory. Quantitative research can be used for theory development when the theory of interest focuses on the causal order of events and behaviors rather than the substance of those events/behaviors. Even then, however, the application is usually limited to reducing the number of possible orders rather than pinpointing the exact causal model.