The given data set is:
\[
\{1100, 1200, 1300, 1500, 2200, 2800, 3500, 3800, 4100, 4200, 4500, 4700, 4800, 5100, 5200, 5300, 5400, 5700, 5800, 6400, 6500, 6600, 6700, 6900, 7000, 7100, 7200, 7300, 7500, 7800, 8200, 8300, 8400, 8500, 8600, 8700, 9000\}
\]
To find the \(74^{\text{th}}\) percentile, we use the formula for rank:
\[
\text{Rank} = Q \times (N + 1)
\]
where \(Q = 0.74\) and \(N = 37\) (the number of data points). Thus,
\[
\text{Rank} = 0.74 \times (37 + 1) = 0.74 \times 38 = 28.12
\]
The rank \(28.12\) indicates that the \(74^{\text{th}}\) percentile lies between the \(28^{\text{th}}\) and \(29^{\text{th}}\) values in the sorted data set. These values are:
\[
X_{\text{lower}} = 7300 \quad \text{and} \quad X_{\text{upper}} = 7500
\]
Using the averaging formula:
\[
Q = \frac{X_{\text{lower}} + X_{\text{upper}}}{2} = \frac{7300 + 7500}{2} = \frac{14800}{2} = 7400.0
\]
The \(74^{\text{th}}\) percentile, \(P_{74}\), is:
\[
\boxed{7400.0}
\]