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Statistics with R and RStudio

Key Information

Module code
ISSU1063
Taught during
Session 1
Module leader
Dr Lucio Vinicius
Pre-requisites
GPA of around 3.3/4.0 (US) or equivalent
Assessment method
In-class quizzes (25%), Final examination (75%)
Download syllabus (PDF)

Module overview

We are exposed to statistical data on a daily basis in the form of opinion polls, economic forecasts, reports on the effect of diet and lifestyle on life expectancy and disease risk, debates over the evidence for climate change, among others. This module introduces statistics and the free software R/RStudio to students with no previous knowledge of mathematics beyond high school level. The module also assesses the uses, misuses and limitations of statistical methods. Topics range from basic descriptive statistics to more advanced topics including multivariate analysis, logistic regression, and model optimisation. As additional skills, students are introduced to professional-standard plotting resources, basic programming functions in R, and the user-friendly RStudio interface.

Learning outcomes

Upon successful completion of this module, students will:

  • Be able to run statistical analyses ranging from simple descriptive statistics to logistic regression models
  • Have acquired in-depth knowledge of R software and its RStudio interface
  • Be able to evaluate the meaning, uses and limitations of statistical techniques
  • Have produced publication-standard statistical plots
  • Exhibit basic knowledge of R programming functions

Module prerequisites

This is a level one module (equivalent to first year undergraduate). Students must have completed one year of undergraduate study. No prior subject knowledge is required for this module, but students are expected to have a keen interest in the area.

Module hours

Classes (usually three or four hours per day) take place on the Bloomsbury campus from Monday to Friday any time between 9am and 6pm.

Assessment

  • In-class quizzes (25%)
  • Final examination (75%)

Module leader

Dr Lucio Vinicius joined UCL Anthropology in 2012, having been previously an Affiliated Lecturer and Research Fellow at Cambridge University (2002-11) and a Research Fellow at the Max Planck Institute (2011-12). He has published articles in Science, Nature Human Behaviour, PNAS among others, and a book by Cambridge University Press. Dr Vinicius was awarded a Teaching Excellence Departmental Award at Cambridge University (2008) and a Provost’s Individual Teaching Award at UCL (2015) for his reformulation of statistics teaching at UCL Anthropology.

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