Step 1 :First, we need to find the z-score that corresponds to a 98% confidence interval. This value is approximately \(2.33\).
Step 2 :The formula for a confidence interval is \(CI = \bar{x} \pm Z \cdot \left(\frac{\sigma}{\sqrt{n}}\right)\), where \(\bar{x}\) is the sample mean, \(Z\) is the z-score, \(\sigma\) is the standard deviation, and \(n\) is the sample size.
Step 3 :In this case, \(\bar{x} = 0.511\), \(Z = 2.33\), \(\sigma = 0.0598\), and \(n = 15\).
Step 4 :We first calculate the value of the standard deviation divided by the square root of the sample size: \(\frac{\sigma}{\sqrt{n}} = \frac{0.0598}{\sqrt{15}} = 0.0154\).
Step 5 :Then, we multiply this value by the z-score: \(Z \cdot \left(\frac{\sigma}{\sqrt{n}}\right) = 2.33 \cdot 0.0154 = 0.0359\).
Step 6 :Finally, we add and subtract this value from the sample mean to find the confidence interval: \(CI = 0.511 \pm 0.0359\).
Step 7 :So, the 98% confidence interval for the population mean lead concentration is \(\boxed{(0.475, 0.547)}\), rounded to three decimal places.