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This module aims to provide you with an opportunity to develop an appreciation of management research in theory and practice. There are two broad objectives: (1) to enhance your knowledge of the research process and enable you to be aware of the problems associated with research, and (2) to prepare you to carry out your own research, in most cases your dissertation.

This module aims to provide you with an opportunity to develop an appreciation of management research in theory and practice. There are two broad objectives: (1) to enhance your knowledge of the research process and enable you to be aware of the problems associated with research, and (2) to prepare you to carry out your own research, in most cases your dissertation.

This module aims to provide you with an opportunity to develop an appreciation of management research in theory and practice. There are two broad objectives: (1) to enhance your knowledge of the research process and enable you to be aware of the problems associated with research, and (2) to prepare you to carry out your own research, in most cases your dissertation.

It is important that we provide bioinformatic cell analysis training to students to significantly improve research possibilities in their future careers in Biomedical Sciences. The quantitative cell biology (QCB) module will focus on the practical use of the methods employed, rather than focussing on just the mathematics and statistical approaches underpinning them. Some of the mathematics and statistics will be discussed, but no prior knowledge will be assumed. The analyses will predominantly be conducted using the R project for statistical computing software (https://www.r-project.org).

Students with or without experience of R programming and/or mathematics will be enrolled on this course.

Students with no background in this area will not be disadvantaged, as they will be provided with computing support, and training via attendance on a data carpentry course delivered by the Southampton Research Software Group (https://rsgsoton.net), to succeed.

There is no opportunity to repeat the year on this programme.

It is important that we provide bioinformatic cell analysis training to students to significantly improve research possibilities in their future careers in Biomedical Sciences. The quantitative cell biology (QCB) module will focus on the practical use of the methods employed, rather than focussing on just the mathematics and statistical approaches underpinning them. Some of the mathematics and statistics will be discussed, but no prior knowledge will be assumed. The analyses will predominantly be conducted using the R project for statistical computing software (https://www.r-project.org).

Students with or without experience of R programming and/or mathematics will be enrolled on this course.

Students with no background in this area will not be disadvantaged, as they will be provided with computing support, and training via attendance on a data carpentry course delivered by the Southampton Research Software Group (https://rsgsoton.net), to succeed.

There is no opportunity to repeat the year on this programme.

This module familiarises students with the main empirical methodologies used in addressing economic question and in analysing and evaluating economic policy. Econometric methods will presented and applied to actual economic issues, including using appropriate statistical software.

This module familiarises students with the main empirical methodologies used in addressing economic question and in analysing and evaluating economic policy. Econometric methods will presented and applied to actual economic issues, including using appropriate statistical software.

The purpose of this module is to provide you with the necessary skills to undertake quantitative research in finance. In particular, we focus on analysing financial markets and firms’ investment and financing decisions. Lectures will introduce a broad range of topics (e.g. ARCH/GARCH). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications to finance. The module is a compulsory module on the MSc Finance. The module introduces empirical methods used in finance and is a prerequisite for Advanced Time Series Modelling in the 2nd semester. In particular, cross-sectional, panel and time series methods are introduced and applied to financial data. The module will introduce methods developed in econometrics and apply these methods to financial data. The module will stress the relationship between finance, econometrics and statistics. The module will only be offered on the MSc Finance. The module provides an introduction to time series modelling, which will be extended in the optional module Advance Time Series Modelling (MANG6297).

The purpose of this module is to provide you with the necessary skills to undertake quantitative research in finance. In particular, we focus on analysing financial markets and firms’ investment and financing decisions. Lectures will introduce a broad range of topics (e.g. ARCH/GARCH). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications to finance. The module is a compulsory module on the MSc Finance. The module introduces empirical methods used in finance and is a prerequisite for Advanced Time Series Modelling in the 2nd semester. In particular, cross-sectional, panel and time series methods are introduced and applied to financial data. The module will introduce methods developed in econometrics and apply these methods to financial data. The module will stress the relationship between finance, econometrics and statistics. The module will only be offered on the MSc Finance. The module provides an introduction to time series modelling, which will be extended in the optional module Advance Time Series Modelling (MANG6297).

The purpose of this module is to provide you with the necessary skills to undertake quantitative research in finance. In particular, we focus on analysing financial markets and firms’ investment and financing decisions. Lectures will introduce a broad range of topics (e.g. ARCH/GARCH). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications to finance. The module is a compulsory module on the MSc Finance. The module introduces empirical methods used in finance and is a prerequisite for Advanced Time Series Modelling in the 2nd semester. In particular, cross-sectional, panel and time series methods are introduced and applied to financial data. The module will introduce methods developed in econometrics and apply these methods to financial data. The module will stress the relationship between finance, econometrics and statistics. The module will only be offered on the MSc Finance. The module provides an introduction to time series modelling, which will be extended in the optional module Advance Time Series Modelling (MANG6297).