#### Department

Statistics Department

#### Degree Name

BS in Statistics

#### Date

5-2012

#### Advisor(s)

Soma Roy

#### Abstract/Summary

As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful graphical abilities that would allow students to visualize their data and the effects of simulating no association on their data. Utilizing R would also allow students to read in their own data in order to further explore analyses and see more examples rather than just built in datasets as with other applets. Finally, simulation-based instruction that R is capable of does not necessarily need a formal test-statistic unlike other methods of instruction. This would allow students to use more intuition in learning statistical concepts.

Unfortunately, there are several challenges to using R in the classroom. Primarily, the user interface is designed around coding. This abstracts the important statistical concepts that students are trying to learn. Many times, students try to learn the code rather than learn the relevant statistics and end up not learning from the technology. This was the key motivation for my project. The idea was that I would build a graphical user interface (GUI) on top of R to allow students to explore statistical concepts and be exposed to R.

As such, I created five applets to allow students to explore simulation and distribution based tests found in introductory statistics courses:

- 2x2 Table
- 2x3 Table
- rxk Table
- Regression
- One-Way Analysis of Variance

These applets have the benefit over other similar approaches in that they allow students to see the animation of the effect of each repetition on simulation of no association, students do not need to have any knowledge of code or programming to utilize the applets, and most importantly, students and instructors have the ability to use their own data sets.

After utilizing several of these applets in introductory statistics courses, students responded very positively. Specifically, a survey was distributed to students following use of the ANOVA applet on a lab and on a homework assignment. The survey indicated that the project was a resounding success. Further, all students recommended use of the applets in future statistics courses. Specifically, students felt that it was helpful in furthering their knowledge of ANOVA. Students felt that it was particularly helpful because of the step-by-step animation showed students the simulation as it was happening. It allowed students to understand what was occurring in a much more visual fashion. Some students even preferred the applets over other packages like Minitab that students were more familiar with due to the straightforward and visual nature. Finally, students also recommended that statistics professors use the applet in future courses, as well.

**URL:** https://digitalcommons.calpoly.edu/statsp/22

#### Included in

Applied Statistics Commons, Categorical Data Analysis Commons, Design of Experiments and Sample Surveys Commons, Higher Education and Teaching Commons, Junior High, Intermediate, Middle School Education and Teaching Commons, Other Statistics and Probability Commons, Probability Commons, Science and Mathematics Education Commons, Secondary Education and Teaching Commons, Statistical Methodology Commons, Statistical Models Commons, Statistical Theory Commons