Describe the abstract idea of a sampling distribution and how it reflects the sample to sample variability of a sample statistic or point estimate. Identify the ...

Central Limit Theorem: A sampling distribution of the mean is approximately normally distributed if the sample size is sufficiently large. This is true no matter what the population distribution is.

Example 1: The population from which samples are selected is {1,2,3,4,5,6}. This population has a mean of 3.5 and a standard deviation of 1.70783. The next display shows a histogram of the population.

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

When an experiment is reproduced we almost never obtain exactly the same results. Instead, repeated measurements span a range of values because of biological variability and precision limits of ...

The normal distribution (also known as the Gaussian distribution) is arguably the most important distribution in Statistics. It is often used to represent continuous random variables occurring in ...