data

(redirected from Categorical data)
Also found in: Dictionary, Thesaurus, Medical, Encyclopedia.
Related to Categorical data: Numerical data

data

for the puposes of data protection legislation, data is information which is being processed by means of equipment operating automatically in response to instructions given for that purpose, is recorded with the intention that it should be processed by means of such equipment, or is recorded as part of a relevant filing system or with the intention that it should form part of a relevant filing system. It need not be held on a computer.
References in periodicals archive ?
Comparing the linear model with the threshold applied to categorical data, using the DIC criteria, and the BF, it was observed that the threshold DIC model showed values equal to 421.00 and 706.74 (Table 2), whereas the linear model presented 956.44 and 1,176.10 for BCS and MRE, respectively.
The k-modes clustering algorithm [3] is an extension of the fc-means algorithm for clustering categorical data by using a simple dissimilarity measure.
The analysis of categorical data: Fisher's exact test.
When conducting structural equations modeling (SEM) with categorical data, the analysis must be based on the correct correlations, the polychoric correlation matrix.
Hypothesis tests concerning the independence of categorical data are performed using the test statistics [lambda]2 (Pearson statistics--Pearson Chi-square).
One method of assigning a score to these ordinal categorical data is to assign a score to ordinal categorical data subjectively (e.g., 5 for strongly agree, 4 for agree, 3 for no opinion, 2 for disagree, and 1 for strongly disagree).
For categorical data, logistic regression is a natural choice and has the advantage of accurately modelling the distribution of the missing data given the observed data.
Categorical data assumes discrete values, whereas continuous data can assume an infinite number of values.
* working with and understanding categorical data is easier than working with and understanding numerical data, and
(2003): Categorical Data Analysis with SAS and SPSS Applications.
In addition, real world datasets contain numerical and categorical data. As a matter of fact most of the QID attributes in micro-data are assumes to be categorical [13].