8221 modules
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ARCH3042 2027-28
Ecology of Human Evolution: Biological, social and cultural approaches to hominin adaptations.
This module explores human evolution in terms of physiological, social and cultural adaptations. It explores human ecology in the broad sense, combining not just cultural and social variability, but also physiological adaptations in past and present-day hunter-gatherers and great apes. These physiological adaptations are not just skeletal, but are also reflected in soft tissues and in surviving genotypes. We shall cover six main themes: different models of biocultural change; Human Behavioural Ecology; hominin energy budgets; brain size changes; dexterity, handedness and tool-use; social organisation over time and space. Evidence derived from primatology, ethnoarchaeology, ancient DNA, stable isotopes and Palaeolithic assemblages can be used to test models such as the Social Brain hypothesis, Daily Energy Expenditures, hominin thermoregulation and mobility/locomotion costs, and the applicability of different evolutionary mechanisms to change in the archaeological record (e.g. Lamarck versus Darwin). Lectures will be augmented by student-led seminars on key debates in palaeoanthropology and Human Behavioural Ecology. -
ARCH3042 2028-29
Ecology of Human Evolution: Biological, social and cultural approaches to hominin adaptations.
This module explores human evolution in terms of physiological, social and cultural adaptations. It explores human ecology in the broad sense, combining not just cultural and social variability, but also physiological adaptations in past and present-day hunter-gatherers and great apes. These physiological adaptations are not just skeletal, but are also reflected in soft tissues and in surviving genotypes. We shall cover six main themes: different models of biocultural change; Human Behavioural Ecology; hominin energy budgets; brain size changes; dexterity, handedness and tool-use; social organisation over time and space. Evidence derived from primatology, ethnoarchaeology, ancient DNA, stable isotopes and Palaeolithic assemblages can be used to test models such as the Social Brain hypothesis, Daily Energy Expenditures, hominin thermoregulation and mobility/locomotion costs, and the applicability of different evolutionary mechanisms to change in the archaeological record (e.g. Lamarck versus Darwin). Lectures will be augmented by student-led seminars on key debates in palaeoanthropology and Human Behavioural Ecology. -
ARCH3042 2025-26
Ecology of human evolution: biological, social and cultural approaches to hominin adaptations.
This module explores human evolution in terms of physiological, social and cultural adaptations. It explores human ecology in the broad sense, combining not just cultural and social variability, but also physiological adaptations in past and present-day hunter-gatherers and great apes. These physiological adaptations are not just skeletal, but are also reflected in soft tissues and in surviving genotypes. We shall cover six main themes: different models of biocultural change; Human Behavioural Ecology; hominin energy budgets; brain size changes; dexterity, handedness and tool-use; social organisation over time and space. Evidence derived from primatology, ethnoarchaeology, ancient DNA, stable isotopes and Palaeolithic assemblages can be used to test models such as the Social Brain hypothesis, Daily Energy Expenditures, hominin thermoregulation and mobility/locomotion costs, and the applicability of different evolutionary mechanisms to change in the archaeological record (e.g. Lamarck versus Darwin). Lectures will be augmented by student-led seminars on key debates in palaeoanthropology and Human Behavioural Ecology. -
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. -
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. -
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. -
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.