If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…

Understanding the concept of the sampling distribution of a statistic is essential for the understanding of inferential procedures. Unfortunately, this topic proves to be a stumbling block for students in introductory statistics classes. In efforts to aid students in their understanding of this concept, alternatives to a lecture-based mode of…

Using Microsoft® Excel, several interactive, computerized learning modules are developed to illustrate the Central Limit Theorem's appropriateness for comparing the difference between the means of any two populations. These modules are used in the classroom to enhance the comprehension of this theorem as well as the concepts that provide the…

Describes the background, development, and testing of a computer software program designed to teach principles of statistical sampling in social science courses. Compares results of a field test of the program, Introduction to Sampling Error Experiments (ISEE), with traditional instruction. (CFR)