Statistical Inference

Module code: EC1012
Module co-ordinator: Dr Martin Foureaux Koppensteiner

Analysis of data often relies on samples to represent a larger set of data. For example, surveys of a limited number of companies or households provide information about an entire country. Statistical inference is the process of drawing conclusions from data that are subject to random variation such as observational errors or sampling variation. Inferential statistics allows us to make predictions about the entire population based on the samples we have available and to test hypotheses and make estimations using the sample data.

Topics covered

  • Samples and populations
  • Random sampling  
  • Central limit theorem
  • Point and interval estimation
  • Hypothesis testing
  • Analysis of variance
  • Regression analysis and the method of least squares


  • 20 one-hour lectures
  • 15 one-hour tutorials


  • Coursework (20%)
  • Exam, 90 minutes (80%)