Abstract:

Striking the right balance between the applications and the theoretical content taught in statistics courses at the undergraduate level was always a problem for statistics education. In this paper we discuss the advantages and challenges of including an experiential learning component in a Time Series introductory course.

Employability remains one of the most important goals of an undergraduate degree. In this context, for students majoring in statistics, it is essential to include as part of their training practical experience for the analysis of real-world data. There are many sources of time series data, such as the evolution of the stock market values over a period of time, or recorded weather-related data (for example temperatures or the amount of precipitation over time). A step forward is to not only use real-world data, but also to require the completion of a term project suggested by a community partner.

For the time series course the community partners provide the data and a list of questions relevant to them. The students must clean the data, select the relevant observations for the questions included in the project, fit several time series models, get predictions based on these models, choose the best model, and analyze and interpret the results. The community partners are available during the term to clarify any aspects related to the data or the questions included in the project. They participate to the final presentations, give students feedback, and get access to the final report and the computer code for data analysis.

For the students working with a community partner offers many opportunities in terms of gaining hands-on relevant practical experience. It comes also with several challenges, such as data cleaning might take more efforts than the actual work with time series models. In this paper we discuss strategies regarding the selection of the projects and organizing the communication with the community partners to ensure the maximum benefits for the students and the community partners involved. We also present a qualitative study based on the students’ feedback about this type of experiential learning.

Keywords:

Experiential learning, undergraduate education, community partners, statistics.