Question

the table below shows the conditional relative frequencies of a set of data comparing gender and whether an academic scholarship was earned. which conclusion can be drawn from the table? an association cannot be determined because 0.47 is close to 0.52. there is an association between gender and scholarship earned because each row adds to 1. an association cannot be determined because 0.47 is close to 0.53. there is an association between gender and scholarship earned because each column total is the average of the values in the column.
scholar-ship\tno scholar-ship\ttotal
male\t0.47\t0.53\t1
female\t0.52\t0.48\t1
total\t0.495\t0.505\t1

Explanation:

Step1: Analyze association concept

In conditional - relative frequency tables, if the conditional relative frequencies for different categories of one variable are different for different categories of the other variable, there is an association. Here, the proportion of males who earned a scholarship (0.47) is different from the proportion of females who earned a scholarship (0.52). Just because values are close does not mean there is no association. Also, the fact that rows add to 1 is a property of conditional - relative frequency tables and not a criterion for association.

Answer:

There is an association between gender and scholarship earned because the conditional relative frequencies for males and females who earned a scholarship are different.