First, let's calculate the mean for each of the given samples:
1. R, B: (15,000 + 18,000) / 2 = 16,500 (already given)
2. R, G: (15,000 + 22,000) / 2 = 18,500 (already given)
3. R, W: (15,000 + 20,000) / 2 = 17,500 (already given)
4. B, G: (18,000 + 22,000) / 2 = 20,000 (already given)
5. B, W: (18,000 + 20,000) / 2 = 19,000 (already given)
6. G, W: (22,000 + 20,000) / 2 = 21,000 (already given)
Now, let's calculate the mean of all six sample means:
(16,500 + 18,500 + 17,500 + 20,000 + 19,000 + 21,000) / 6 = 112,500 / 6 = 18,750
The mean of all six sample means is 18,750.
Next, let's calculate the population mean:
(15,000 + 18,000 + 22,000 + 20,000) / 4 = 75,000 / 4 = 18,750
The population mean is 18,750.
Since the mean of all six sample means is equal to the population mean (18,750), the sample mean is an unbiased estimator of the population mean.