A pivotal theorem which is of critical importance to statistical inference in probability and statistics is the Central Limit Theorem (CLT). The theorem concerns the sampling distribution of random samples taken from a population, including population distributions that do not have to be normal distributions. This paper contains a brief history of the CLT; several forms of the CLT--Kreyszig, Groeneveld, Rahman, Harnett, Dubewicz, and Marzillier; and a proof of the CLT. Examples, both using a small population with hand calculations and using large populations with computer programs, are included to illustrate concepts of the CLT. A HyperCard stack and the program "Resampling Stats" are also demonstrated in the paper. The appendixes contain a proof of Form 5 CLT, a computer worksheet on CLT, three examples of the CLT HyperCard, and a computer program. (Contains 14 references.) (Author/ALF)