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Unit of study_

ECMT3160: Statistical Modelling

2022 unit information

This unit provides an accessible foundation in the principles of probability and mathematical statistics that underlie econometric methodologies. Its objective is to develop a deeper understanding of econometric methodologies encountered in intermediate units of study. The unit starts with the notion of a simple random experiment and extends it to the notion of datagenerating process for observational data in econometrics. The core topics of this unit include distribution finding techniques, identification in parametric and semiparametric models, estimation theory, and hypothesis testing, Monte Carlo techniques and the bootstrap.

Unit details and rules

Managing faculty or University school:

Arts and Social Sciences

Study level Undergraduate
Academic unit Economics
Credit points 6
Prerequisites:
? 
ECMT2150 or ECMT2950 or ECMT2110 or ECMT2010
Corequisites:
? 
None
Prohibitions:
? 
ECMT3620 or ECMT3720 or ECMT3210
Assumed knowledge:
? 
None

At the completion of this unit, you should be able to:

  • LO1. understand basic ideas and methods of probability
  • LO2. understand notions of statistical independence and conditioning
  • LO3. understand counting methods and other combinatorics, and ways of using them.
  • LO4. understand notions of random variable and probability distribution, and ways of using them.
  • LO5. understand notions of random vectors and their distributions, weak law of large numbers, and central limit theorem, and their use in statistical approximation.

Unit availability

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The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.

There are no availabilities for this year.
Session MoA ?  Location Outline ? 
Semester 1 2020
Normal day Camperdown/Darlington, Sydney
Outline unavailable
Semester 1 2021
Normal day Camperdown/Darlington, Sydney
Semester 1 2021
Normal day Remote
Semester 1 2022
Normal day Camperdown/Darlington, Sydney
Semester 1 2022
Normal day Remote

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Modes of attendance (MoA)

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