Journal of The Korea Society of Computer and Information Vol. 21 No. 7, pp. 85-92, July 2016 www.ksci.re.kr http://dx.doi.org/10.9708/jksci.2016.21.7.085 The law of large numbers, central limit theorem, and connection among binomial distribution, normal distribution, and statistical estimation require dynamics of continuous visualization for students’ better understanding of the concepts. During this visualization process, the differences and similarities between statistical probability and mathematical probability that students should observe need to be provided with the intermediate steps in the converging process. We propose a visualization method that can integrate intermediate processes and results through Excel. In this process, students’ experiences with dynamic visualization help them to perceive that the results are continuously changed and extracted from multiple situations. Considering modeling as a key process, we developed a classroom exercise using Excel to estimate the population mean and standard deviation by using a sample mean computed from a collection of data out of the population through sampling. Mathematical thinking often involves various visuals that aid in developing an understanding of mathematical objects help students make sense of abstract mathematics concepts and thus motivate their learning and participation in the classroom ([1], [2]). Multiple representations as visual mediators facilitate students’ deeper understanding of mathematical concepts ([3]). An efficient way of representing visual mediators is to employ multiple representations through the use of technology. However, there has been limited awareness of the need for using technology in the classroom, where many mathematical concepts are taught in a lecture style that may not reflect students’ various ways of learning. Among various mathematical subjects, the ambiguity and uncertainty of the concepts of probability has been particularly difficult for students to learn. Moreover, teachers tend to teach concepts in probability and statistics by providing definitions and theorems in an abstract way and focusing on computation which may not help students understand the concept of probability deeply or may even hinder students to see the concept’s connection to real-life situations ([4], [5], [6]). The appropriate use of technology for continuous visualization in teaching and learning concepts in probability and statistics may help overcome these difficulties. In particular, in teaching and learning the differences and similarities between statistical probability and mathematical probability, which is a difficult but crucial concept, technology can be an instrument in generating dynamic processes where statistical probability converges to mathematical probability. To this end, it would be helpful to design experiments involving simulations of such processes with the use of random numbers, in which students can predict the mathematical probability. This would make the relation between the two types of probabilities more accessible ([7], [8]). Various class materials have been developed that