Conditional+Distrobution

The effect of the change in the independent variable is seen in the dependent variable which are kept in the x (Row) and Y (column) respectively in a table. This is known as the conditional distribution of Y with respect to X. In other words the within column frequency distribution is known as conditional distribution. This represents the association between the two variables. Following is the example to illustrate the conditional distribution.

The sample of 120 people of different age groups ranging from 15 to above 30 is taken and they were surveyed if they drink alcohol. The result illustrates that as the age of the person increases that also increases their abuse of the alcohol. Simply it can be said that the change in X-values definitely causes change in the value of Y as well. This is the conditional distribution. Their association can also be detected by the chi-square test. The non-zero value of chi shows some kind of association always.
 * Age Range(X) || 15-20 || 20-25 || 30- ||
 * Alcohol consumption(Y) ||^  ||^   ||^   ||
 * Yes || 20 || 30 || 40 ||
 * No || 5 || 15 || 10 ||