1. First a confidence interval is constructed without using the finite population correction factor. Then, for the same identical data, a confidence interval is constructed using the finite population correction factor. The width of the interval without the finite population correction factor is wider than the confidence interval with the finite population correction factor.
2. When the population is normally distributed and the population standard deviation μ is unknown, then for any sample size n, the sampling distribution of is based on the t distribution.
3. When the level of confidence and sample standard deviation remain the same, a confidence interval for a population mean based on a sample of n = 200 will be wider than a confidence interval for a population mean based on a sample of n = 150.
4. When the level of confidence and the sample size remain the same, a confidence interval for a population mean µ will be wider, when the sample standard deviation s is small than when s is large.
5. When the level of confidence and sample standard deviation remain the same, a confidence interval for a population mean based on a sample of n = 100 will be narrower than a confidence interval for a population mean based on a sample of n = 50.
6. The sample mean, the sample proportion and the sample standard deviation are all unbiased estimators of the corresponding population parameters.
7. Assuming the same level of significance α, as the sample size decreases, the value of t α/2 approaches the value of zα/2.