Two Learning Activities for a Large Introductory Statistics Class

Abstract

In a very large Introductory Statistics class, i.e. in a class of more than 300 students, instructors may hesitate to apply active learning techniques, discouraged by the volume of extra work. In this paper two such activities are presented that evoke student involvement in the learning process. The first is group peer teaching and the second is an in-class simulation of random sampling from the discrete Uniform Distribution to demonstrate the Central Limit Theorem. They are both easy to implement in a very large class and improve learning.

Maximizing a Probability: A Student Workshop on an Application of Continuous Distributions

“…If time was at a premium, as was the case here, then each group may consider in detail just one or two of the aforementioned distributions. This scenario presents an excellent opportunity for peer-teaching to take place, as espoused in Zacharopoulou (2006). Indeed, our session ended with each group providing an account of their solution to the problem for the particular distributions they had studied, a coherent argument for or against the use of these distributions to model the longevity of a torch and, with justification, a nomination for the most suitable distribution.…”

Practices of the Random Variable Proposed in the Chilean Mathematics Curriculum of Secondary Education

“…Some studies on the random variable have focused on showing examples of activities that promote the idea of the discrete random variable [5,6], whereas others deal with the conceptual understanding of the idea of the random variable and the connections or links with other concepts, such as estimators, parameters, probability distribution, sampling distribution, unbiased estimators, and expected values [7]. There are also studies that propose activities in which it is necessary for students to have prior knowledge about the random variable for the study of probability distributions (such as binomial, normal and exponential), and framed within them the characteristics of the binomial random variable [8][9][10].…”