BAEcon Economics

Year of entry: 2027

Course unit details:
Applied Statistics for Social Scientists

Course unit fact file
Unit code SOST20142
Credit rating 20
Unit level Level 1
Teaching period(s) Semester 2
Offered by Social Statistics
Available as a free choice unit? Yes

Overview

The main topics to be covered are: 

  • Data exploration and visualization using R
  • Descriptive statistics 
  • Modelling with Continuous Data 
  • Modelling with categorical Variables 

Pre/co-requisites

Applied Statistics for Social Scientists Anti-Requisite: Students who have taken SOST10142 may NOT take SOT20142. Not available to Third Year Students.

Aims

The aims of this course are for each student to achieve:  

  • an introductory to data cleaning and exploration  
  • an understanding of basic statistics tests  
  • an understanding of multivariate statistical analysis  
  • an ability to use statistical software R  

Learning outcomes

  • be able to import and export data in R  
  • be able to prepare data in R  
  • be able to produce visualisations of data  
  • be able to understand and run descriptive statistics in R  
  • be able to understand and run a battery of test of hypothesis in R  
  • be able to understand and run a variety of statistical models in R  

Teaching and learning methods

Lectures, practicals and coursework.  

Please note the information in scheduled activity hours are for guidance only and may change.  

Assessment methods

Online exam - 20 MCQs (25%)

Data Visualisation Report supported by reproducible R code - 1,000 words including reproducible R code (75%)

Feedback methods

Feed-back on individual based essay 

Recommended reading

Agresti, A. (2018). Statistical Methods for the Social Sciences (5th ed.). Pearson. 

Fogarty, B. (2019). Quantitative Social Science Data with R. 

Hothorn, T., & Everitt, B. (2014). A handbook of statistical analyses using R (Third edition). CRC Press, Taylor & Francis Group.  

Landers, R. N. (2019). A step-by-step introduction to statistics for business. SAGE.  

Leon-Guerrero, A., & Frankfort-Nachmias, C. (2018). Essentials of social statistics for a diverse society (Third edition). SAGE. 

Wickham, H., & Grolemund, G. (2017). R for Data Science: import, tidy, transform, visualize, and model data. O’Reilly UK Ltd. 

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 8
Independent study hours
Independent study 172

Teaching staff

Staff member Role
Todd Hartman Unit coordinator

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