Analyses for the contingency tables can be computed from data collected in the contingency tables or directly i.e., from raw data. Whereby it is possible to transform the data from the contingency table to the raw form or vice versa.
Consider a sample consisting of 34 individuals (). We examine 2 traits of these individuals (=sex, =education). Gender appears in 2 categories (=female, =male) education in 3 categories, (=primary + vocational =medium, =higher).
In the case of raw data, when you open the test options window, e.g., the for the tables, the
raw data option will automatically be selected..
For data collected in a contingency table, it is a good idea to select this data (numerical values without headers) before opening the test window. Then, when you open the test window, the
contingency table option will automatically be selected and the data from the selection will be displayed.
In the test window, we can always change the automatically detected setting regarding the form of data organization, as well as enter data into the contingency table from the window.
This is a basic condition for using many statistical tests based on contingency tables, e.g., the chi-square test. This condition implies a large expectred frequencies. According to Cochran's 1952 interpretation1), none of the expected frequencies can be and no more than 20% can be . Information about whether this condition is met (or not) by the data collected in the table can be returned to the report.
Basic tests for contingency tables:
Coefficients for contingency tables:
You can also include a basic summary of the tables in the results report:
In order for such a table to be returned by the program, the option
include analysed data should be selected in the test window. For the data from the example, the contingency table of observed frequencies is as follows:
For the data in the example The contingency table of expected frequencies is as follows: