Sequential vs. Simultaneous: Approaches to Learning Programming and Statistics

Robert S. Young; Rebecca L. Colquhoun; Tiago A. Marques; Brittany Blankinship; Ozan Evkaya; William P. Kay

doi:10.2218/ED.9781836450795

Sequential vs. Simultaneous: Approaches to Learning Programming and Statistics

Authors

Robert S. Young

Edinburgh Medical School, University of Edinburgh; Zhejiang University - University of Edinburgh (ZJE) Institute

Rebecca L. Colquhoun

Department of Earth Science and Engineering, Imperial College London

Tiago A. Marques

Departamento de Biologia Animal, Faculdade de Ciências da Universidade de Lisboa; Centre for Research into Ecological and Environmental Modelling, University of St Andrews

Brittany Blankinship

Edinburgh Medical School, The University of Edinburgh

Ozan Evkaya

School of Mathematics, University of Edinburgh

William P. Kay

School of Biosciences, Cardiff University

DOI: https://doi.org/10.2218/ED.9781836450795.18

Synopsis

Within many statistics modules, programming is presented as a tool which students need to learn quickly, engage with briefly, and then move on from. Yet, both statistics and programming come with a heavy cognitive load and are sources of angst, anxiety, and confusion for students. This chapter compares three approaches to teaching statistics and programming for students who need to know both. This chapter is for anyone designing (or re-designing) a course teaching both programming and statistics. With concrete examples from the author’s diverse experiences, this chapter presents a practical guide as well as an opportunity to learn from others who have been there before.