Answer:
The appropriate point estimate of μ (the population mean) is the **sample mean** (option 1).
Here's a brief explanation of each option:
1. **Sample mean**: This is the most common point estimate for the population mean. It is calculated by taking the average of the values in your sample. The sample mean is an unbiased estimator of the population mean, assuming that your sample is representative of the population.
2. **Sample standard deviation**: The sample standard deviation provides information about the spread or variability within your sample data. It is not a point estimate of the population mean, but it is useful for understanding the dispersion of your sample data.
3. **Margin of error**: The margin of error is not a point estimate of the population mean. It is typically used in confidence interval calculations to indicate the range within which the true population mean is likely to fall.
4. **Standard error of the mean**: This is also not a point estimate of the population mean. It is a measure of how much the sample mean is expected to vary from one sample to another. It is often used in conjunction with confidence intervals and hypothesis testing but does not directly estimate the population mean itself.
So, in summary, the appropriate point estimate for μ is the sample mean.
Explanation: