By Craig Lazarski & Jeffery Painter (Cary Academy)
Abstract
Using R/Shiny I developed several explorations of statistical concepts explored in an introductory statistics course to explore fundamental ideas of inference, experimental design, and the central limit theorem. The dice app allows students to explore dice created by several companies and determine if they are fair or not. The R shiny app allows students to simulate rolling the dice many times and from this they can assess the distribution of outcomes and make inferences. This app encourages students to explore hypothesis testing informally and promotes the development of the ideas of errors in testing and power. The central limit theorem app asks students to explore how to make inferences from populations when the population distributions are unknown. Students will develop an understanding of the central limit theorem and explore the relationship between the standard deviation of the sampling distribution and the standard deviation of the population. Students should develop a deeper understanding of the importance of the central limit theorem and how it allows inferences to be made when population distributions are unknown. The blocking app expands on a Free Response question from the AP Statistics exam involving planting fruit trees near a forest. Students simulate the results of two types of tree production under different varying conditions, compare the resulting distributions, and understand how blocking reduces variation. Students are able to explore in detail the characteristics of sampling distributions produced by each type of blocking design and develop an understanding of when blocking is most effective.