Final answer:
To analyze the relationship between SES and asthma, a SAS data set is created and a chi-square test is conducted to determine any statistically significant association between these variables, utilizing the chi-square distribution as a key statistical tool in public health research.
Step-by-step explanation:
To evaluate the relationship between socioeconomic status (SES) and asthma using SAS 3.7, we start by creating a SAS data set with the provided summary data. Once the data is in place, we can perform a chi-square test to determine if there's a statistically significant association between the SES groups and the incidence of asthma. This process involves using PROC FREQ in SAS to calculate the chi-square statistic and p-value from the contingency table that cross-tabulates SES groups with asthma occurrence. If the p-value is less than the chosen level of significance (often 0.05), we would reject the null hypothesis and conclude that there is a relationship between SES and asthma.
To address a given problem, including assessing relationships such as SES and health outcomes like asthma, the chi-square distribution is a robust statistical tool. In education settings, it allows us to determine if actual data fit an expected distribution or if there are significant differences or relationships in categorical data, providing essential insights into health disparities and other public health concerns.