050, a correlation exists between the tested variables of “Intestinal cancer result” and “Age.” Table 2: P-values of the coefficients of the example dataīecause the p-value of the Chi Square coefficient is smaller than the significance level of. The answer to the questions can be found with the help of a schematic representation, which in this case looks as follows: The data is on 406 persons who had a colonoscopy (intestinal screening). The question is examined based on a dataset provided by the Statistical Analysis Institute (SAS). The procedure of the chi-square contingency analysis is summarized in three steps, which are described in the following section. Is there a correlation between age and the likelihood of getting intestinal cancer? This chapter explains in detail the procedure of the chi-square contingency analysis based on the following question: Here, cross tables can be used for calculating the various coefficients that reflect the size and direction of the correlations. The chi-square contingency analysis is an extension of the “classical” cross-table test that examines each of two attributes against two characteristics. Pearson’s chi-square test of independence is a non-parametric statistical procedure with a chi-square-distributed test statistic that is used for testing the mutual dependency of two attributes. Chi-square contingency analysis with SPSS
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