8596 modules
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PSYC6055 2026-27
Statistical Programming in R
The Statistical Programming in R Module is focused on extending existing skills in analyzing data from quantitative research. The focus of this course will not be on extensively expanding the mathematical knowledge of the techniques employed but will be on acquiring practical skills such as scripting, flexible matrix manipulation and advanced visualization. All these skills are particularly useful when confronted with especially large datasets, and when confronted with a multitude of repetitive statistical
procedures needing implementation. This module will also cover an introduction into Linear Mixed Models. Analyses will be implemented using the interactive programming environment known as R. R is a free, open source programming language for statistical analysis. -
STAT6142 2026-27
Statistical Programming in R
This module aims to give students a grounding in the use of statistical software for data manipulation, analysis and simulation in R. -
MATH6026 2025-26
Statistical Seminar Series I
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MATH6026 2026-27
Statistical Seminar Series I
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MATH6026 2027-28
Statistical Seminar Series I
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MATH6028 2027-28
Statistical Seminar Series II
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MATH6028 2025-26
Statistical Seminar Series II
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MATH6028 2026-27
Statistical Seminar Series II
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ECON1007 2026-27
Statistics for Economics
The module is designed to prepare economics students for the econometrics modules taken in their second and third year. The module provides an introduction to the topic of statistics, with particular reference to the use of statistics to address questions in economics. The module content covers both descriptive statistics and statistical inference, leading up to regression analysis.
The course content is typically as follows: describing data; probability; random variables; sampling; estimation; hypothesis testing; simple and multiple regression. -
ECON1007 2025-26
Statistics for Economics
All economics students, on both single and joint honours programmes, take this course. It is optional for students outside of economics. The module is designed to prepare students for the econometrics modules taken in second and third year. It also complements the economics modules taken in by students in first and second year. It provides an introduction to the topic of statistics, with reference to economics examples. It then covers more advanced topics leading up to regression analysis.
The course content is as follows: describing data; probability; discrete random variables; continuous random variables; sampling; estimation; hypothesis testing; simple regression and multiple regression.
One of the pre-requisites for MATH2040, MATH3085, ECON1021, ECON2001, ECON2002, ECON2003, ECON2004, ECON2026 and ECON3016.