To do this project, you should understand the following terms and concepts (do background research to fill in any gaps in your knowledge): 1  binary (base 2), 2  decimal (base 10), 3  hexadecimal (base 16), 4  bit, byte, kilobyte (kB), megabtye (MB), 5  radix (number base).
Sampling distribution. In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given statistic based on a random sample. Sampling distributions are important in statistics because they provide a major simplification en route to statistical inference.
Save. The sampling distribution can be described by calculating its mean and standard error. The central limit theorem states that if the sample is large enough, its distribution will approximate that of the population you took the sample from.This means that if the population had a normal distribution, so will the sample.he sampling distribution can be described by calculating its mean and standard error. The central limit theorem states that if the sample is large enough, its distribution will approximate that of the population you took the sample from.