What Is a Cross Tabulation?

Cross Tabulations is a commonly used subtotal table. Querying data using cross tables is very intuitive and widely used. Cross-tab queries are also a feature of databases.

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Suppose we have two variables, gender (male or female) and chirality (right or left hand). It is further assumed that 100 people are randomly selected from a very large group of people as part of a study of gender differences in opponents. You can create a strain gauge to show the individual numbers of men and right-handers, men and left-handers, women and right-handers, and women and left-handers. Such a strain gauge is shown below.

(1) Multiple columns (historically, they were designed to take up all the spaces on the printed page). Each row refers to a specific subgroup (for example, male) in the population, and these columns are sometimes called banner points (and rows are sometimes called stubs).

(2) In general, any column comparison tests the differences between columns and displays the results using letters, using colors or arrows to identify cells in the table that are highlighted in some way (as shown in the example above).

(3) One or more: percentage, row percentage, column percentage, index or average.

(4) Unweighted sample size (ie count).

The degree of correlation between two variables can be evaluated by multiple coefficients. The simplest, only applicable to the case of 2 × 2 crosstabs, is the phi coefficient defined by:

2 is calculated according to Pearson's chi-square test, and N is the sum of the observed values. changes from 0 (corresponding to no correlation between variables) to 1 or -1 (completely correlated or completely uncorrelated), provided that it is based on frequency data in a 2 × 2 table. Then its sign is equal to the sign of the product of the main diagonal elements of the table minus the product of the off-diagonal elements. If and only if each marginal ratio is equal to .50 (the two diagonal cells are empty), takes the minimum value -1.00 or the maximum value 1.00.

Alternatives include the Quartet correlation coefficient (also only applicable to 2 × 2 tables), the cross coefficient C, Cramér's V.

The disadvantage of C is that it does not reach the maximum value of 1 or the minimum value of -1; the maximum value that can be reached in the 2 × 2 table is 0.707; the maximum value that can be reached in the 4 × 4 table is 0.870. In emergency tables with more categories, it can reach values close to 1. Therefore, it should not be used to compare associations between tables with different numbers of categories. Also, it does not work for asymmetric tables (tables with unequal rows and columns).

The formulas for the C and V coefficients are:

k is the number of rows or columns, whichever is smaller.

Can be divided by C

Fully correlated in a table of any number of rows and columns, bringing its maximum to 1.

The quarter correlation coefficient assumes that the underlying variables of each dichotomy are normally distributed. The quartile correlation coefficient provides "a convenient measure of correlation when the level measurement has been reduced to two categories." The quartile correlation should not be confused with the Pearson product moment correlation coefficient calculated by assignment, for example, values 0 and 1 Represents two levels of each variable (mathematically equal to the phi coefficient). An expansion of the quadrilateral correlation involving more than two rank variables is the multiple correlation coefficient.

The lambda coefficient is a measure of the strength of the crosstab's association when measured at a nominal level. Values range from 0 (no correlation) to 1 (the theoretical maximum possible correlation). Asymmetric lambda measures the percentage improvement predicted by the dependent variable. Symmetric lambda measures the percentage improvement when making predictions in both directions.

The uncertainty coefficient is another measure of the variable at the nominal level. ^[3]

Cross-reports are a common type of reports. They are basic reports, and they are grouped in rows and columns. Another concept involved here is grouped reports. This is the most common and common report type among all reports, and is a report format supported by all reporting tools. In general terms, a grouped report is only a vertical grouping. The traditional grouping report production method is to divide the report into strips. The user specifies the grouping according to a data binding wizard, summarizes the fields, and generates a standard grouping report.