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Create Classification Tables Right-click the fact table column in the Target View and select Create Classification. The Create Classification dialog displays. Enter a name for the classification table and click OK. The table name must be unique (it cannot be the same as any existing tables in the source database).

Cross tabulations are simply data tables that present the results of the entire group of respondents as well as results from sub-groups of survey respondents. Cross tabulations enable you to examine relationships within the data that might not be readily apparent when analyzing total survey responses.

Cross classification usually means that the data points are classified according to multiple criteria (usually coded as factors, that is, categorical variables) at the same time, giving rise to a contingency table.

Classification table. The classification table is another method to evaluate the predictive accuracy of the logistic regression model. In this table the observed values for the dependent outcome and the predicted values (at a user defined cut-off value, for example p=0.50) are cross-classified.

1) It reduces the possibility of errors Creating crosstabs can simplify data sets as they divide the total set into representative subgroups, which can then be interpreted at a smaller, more manageable scale. This reduces the potential for errors when analysing data, making the whole process more efficient.

A contingency table, also known as a cross-classification table, describes the relationships between two or more categorical variables.

A Classification Table (aka a Confusion Matrix) describes the predicted number of successes compared with the number of successes actually observed. Similarly, it compares the predicted number of failures with the number actually observed.