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.
Sampling in Statistical Inference. The use of randomization in sampling allows for the analysis of results using the methods of statistical inference. Statistical inference is based on the laws of probability, and allows analysts to infer conclusions about a given population based on results observed through random sampling.