Data can be represented at four levels of measurement:
Nominale.g., Male/Female; The word nominal means in name only. Nominal variables are used on surveys to describe or identify the population being sampled;
Ordinale.g., Rare, Medium Rare, Medium, Medium Well, Well Done; An ordinal measure can capture how a person feels on an issue, which is the case when the distance between each of the measure cannot be determined scientifically;
Intervale.g., Temperature or 1 to 5 satisfaction scales; with Interval measures, the distance between each unit of measure has a precise distance. For example, how long does it take ten trucks on the loading dock to unload a full container of merchandise?
RatioAge in years, relative time, relative distance or relative temperature. Ratio data is captured with absolute measures; height, weight, distance, and money are all examples of ratio data.
Unit of Analysisa classification of the individual, group, company, or societal unit under study. It is relevant because comparison of data from different units of analysis is frequently used to draw conclusions that while they seem logical are, in fact, erroneous.
For example, predicting the outcome of local elections based on a national survey or predicting the outcome of national elections based on a local survey. This fallacy involving misapplication of the unit of analysis is related to the ecological and exception fallacies. Consider this important issue in research, especially when using secondary data (i.e., data collected by somebody else for a different research question), as it is not always clear whether one is examining the individual, group, company, industry, etc.
For example, news commentators sometimes compare mismatched units of analysis and draw conclusions that may not be correct. If one draws conclusions about a group from one individual case, that is the exception fallacy. If one draws conclusions about an individual b View More »