Module HMB-2017:
Econometrics

Overview

The module will cover the fundamentals of probability theory and of statistical methods. It will introduce the method of ordinary least squares (OLS) used in estimating the quantitative relationship between economic variables, in the context of cross-sectional data. There will be instruction on data management and the use of the statistical and regression tools within Excel.

Assessment Strategy

-threshold -C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills. -good -B- to B+ (60-69%): Very good performance Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills. -excellent -A- to A+ (70%+): Outstanding performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills. -another level-C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.

Learning Outcomes

• Analyse the assumptions underlying the OLS model, and its inherent limitations.

• Apply key statistical concepts.

• Apply the OLS model to cross-sectional data and interpret the results.

• Explain the key properties of various probability distributions.

• Formulate and test hypotheses.

• Organise, present and interpret data in an appropriate manner.