Step 1 :Given that the margin of error (E) is 0.025 and the Z-score for a 90% confidence level is 1.645 (Z).
Step 2 :For part a), since we have no prior research, we can use the formula for the sample size needed for a proportion, which is \(n = \frac{{Z^2 * p * (1-p)}}{{E^2}}\), where p is the estimated proportion. Since we don't have an estimated proportion, we can use p = 0.5, which will give us the maximum sample size needed.
Step 3 :Substituting the given values into the formula, we get \(n = \frac{{(1.645)^2 * 0.5 * (1-0.5)}}{{(0.025)^2}}\).
Step 4 :Calculating the above expression, we find that the sample size needed for part a) is \(\boxed{1083}\).
Step 5 :For part b), we can use the same formula, but this time we have an estimated proportion from a preliminary sample, which is p = 0.225.
Step 6 :Substituting the given values into the formula, we get \(n = \frac{{(1.645)^2 * 0.225 * (1-0.225)}}{{(0.025)^2}}\).
Step 7 :Calculating the above expression, we find that the sample size needed for part b) is \(\boxed{755}\).