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Attributes are closely related to variables. A variable is a logical set of attributes. [1] Variables can "vary" – for example, be high or low. [1] How high, or how low, is determined by the value of the attribute (and in fact, an attribute could be just the word "low" or "high"). [1] (For example see: Binary option)
For example, if a nominal variable has three categories (A, B, and C), two dummy variables would be created (for A and B) where C is the reference category, the nominal variable that serves as a baseline for variable comparison. [6] Another example of this is the use of indicator variable coding that assigns a numerical value of 0 or 1 to each ...
In statistics, a categorical variable (also called qualitative variable) is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property. [1]
As this is a logical (deterministic) and not a statistical (probabilistic) technique, with "crisp-set" QCA , the original application of QCA, variables can only have two values, which is problematic as the researcher has to determine the values of each variable. For example: GDP per capita has to be divided by the researcher in two categories ...
For example, five-, seven- and nine-point scales with a uniform distribution of responses give PCIs of 0.60, 0.57 and 0.50 respectively. The first of these problems is relatively minor as most ordinal scales with an even number of response can be extended (or reduced) by a single value to give an odd number of possible responses.
Qualitative properties are properties that are observed and can generally not be measured with a numerical result, unlike quantitative properties, which have numerical characteristics. Description [ edit ]
Data and information visualization (data viz/vis or info viz/vis) [2] is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount [3] of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items.
It plays an important theoretical role because it opens the way to the simultaneous treatment of quantitative and qualitative variables. Two methods simultaneously analyze these two types of variables: factor analysis of mixed data and, when the active variables are partitioned in several groups: multiple factor analysis.