BAEcon Economics

The main topics to be covered are:

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

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

• 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

Lectures, practicals and coursework.

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

Online exam - 20 MCQs (25%)

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

Feed-back on individual based essay

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.