11312 modules
Page 356
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ECON2034 2027-28
ECON Dissertation: Prelim Info
This is a blended learning module to provide students with the basic tools and information necessary to embark in their third year dissertation modules. -
ECON2034 2026-27
ECON Dissertation: Prelim Info
This is a blended learning module to provide students with the basic tools and information necessary to embark in their third year dissertation modules. -
ECON2041 2026-27
Econometric Theory
The module will familiarise students with the parts of statistical distribution theory and statistical inference that are essential to a full understanding of econometrics and applied statistics. It will give student a thorough introduction to the theoretical concepts underlying modern Econometrics. It develops ideas presented in ECON1007 and ECON1011 and applies mathematical techniques from ECON1008. -
ECON2041 2027-28
Econometric Theory
The module will familiarise students with the parts of statistical distribution theory and statistical inference that are essential to a full understanding of econometrics and applied statistics. It will give student a thorough introduction to the theoretical concepts underlying modern Econometrics. It develops ideas presented in ECON1007 and ECON1011 and applies mathematical techniques from ECON1008. -
ECON2041 2028-29
Econometric Theory
The module will familiarise students with the parts of statistical distribution theory and statistical inference that are essential to a full understanding of econometrics and applied statistics. It will give student a thorough introduction to the theoretical concepts underlying modern Econometrics. It develops ideas presented in ECON1007 and ECON1011 and applies mathematical techniques from ECON1008. -
ECON2042 2026-27
Econometrics with Big Data
The module will proceed from a review of known content (like matrix algebra, linear regression, hypothesis testing) to more advanced topics such as multiple linear regression, heteroscedasticity, restrictions in hypothesis testing, issues of model misspecification, and an introduction to big data techniques such as shrinkage methods to exploit large datasets for statistical inference. The module will thus equip students with fundamental methods for statistical inference on large datasets. -
ECON2042 2027-28
Econometrics with Big Data
The module will proceed from a review of known content (like matrix algebra, linear regression, hypothesis testing) to more advanced topics such as multiple linear regression, heteroscedasticity, restrictions in hypothesis testing, issues of model misspecification, and an introduction to big data techniques such as shrinkage methods to exploit large datasets for statistical inference. The module will thus equip students with fundamental methods for statistical inference on large datasets. -
ECON2042 2028-29
Econometrics with Big Data
The module will proceed from a review of known content (like matrix algebra, linear regression, hypothesis testing) to more advanced topics such as multiple linear regression, heteroscedasticity, restrictions in hypothesis testing, issues of model misspecification, and an introduction to big data techniques such as shrinkage methods to exploit large datasets for statistical inference. The module will thus equip students with fundamental methods for statistical inference on large datasets. -
ECON6093 2025-26
Economic Analysis
This module will familiarise students with the main concepts, methods and insights of microeconomic analysis, with a special focus on their possible applications and policy implications. -
ECON6093 2026-27
Economic Analysis
This module will familiarise students with the main concepts, methods and insights of microeconomic analysis, with a special focus on their possible applications and policy implications.