Assuming non-independence among random variables X1, X2, ..., Xn can lead to significant variance in their average. When all variables are equal, such as X1 = X2 = ... = Xn, the variance of their average becomes equal to the variance of a single variable, which is σ². This results in Var((1/n) * sum from k = 1 to n of Xk) equating to σ², demonstrating that the variance does not diminish with increasing n. Consequently, the variance of the average can exceed σ²/n, contradicting the assumption of independence. This example illustrates the critical impact of variable dependence on variance calculations.