The statistics which are unbiased estimators of population parameters are:
I. A sample proportion that is used to estimate a population proportion.
II. A sample variance that is used to estimate a population variance.
III. A sample mean that is used to estimate a population mean.
In Statistics, an estimator can be defined as a statistical value (quantity), which is typically used for estimating a given parameter.
On the other hand, an unbiased estimator refers to an estimator with an expected value that is equal to the parameter i.e the value of its bias is equal to zero (0).
Typically, the proximity or closeness of a sample statistics to the population parameters is mainly determined through the use of an unbiased estimator.
Generally, the determinants of a probability distribution are referred to as parameters.
Hence, a normal distribution is determined through the use of the following:
- Variance of the population.
In conclusion, the statistics which are unbiased estimators of population parameters are:
I. A sample proportion that is used to estimate a population proportion.
II. A sample variance that is used to estimate a population variance.
III. A sample mean that is used to estimate a population mean.
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