Master of Science in Statistics (Full Dissertation) (98982).
Statistics, Department of Dissertations and Theses in Statistics. PhD candidates: You are welcome and encouraged to deposit your dissertation here, but be aware that 1) it is optional, not required (the ProQuest deposit is required); and 2) it will be available to everyone on the Internet; there is no embargo for dissertations in the UNL DigitalCommons. Master's candidates: Deposit of your.
Statistics MSc is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics. The programme combines in-depth training in mainstream advanced statistical modelling with a broad range of specialisations, from financial mathematics to statistical bioinformatics; from clinical trials to risk management.
The MSc Statistics (Social Statistics) (Research) aims to provide high-level training in the theory and application of modern statistical methods, with a focus on methods commonly used in the social sciences. You will gain insights into the design and analysis of social science studies, including large and complex datasets, study the latest developments in statistics, and learn how to apply.
Dissertation statistics often create anxiety for Masters, Doctoral, and MBA students. Even though your dissertation is about a topic that you should feel comfortable with, it often involves statistical analyses with which you are not. This causes unnecessary tension. The sooner you involve a statistical consultant in the research, the easier the process. Dr Liezel Korf Associates has advised.
Dissertation Support for Postgraduate Masters Students The final stage of your taught postgraduate Masters degree is writing and submitting your dissertation or project report. Here you can find advice on the support that is available to help you to ensure that the process is a smooth one and that you can look ahead to successfully completing your degree.
The Master of Science in Statistical Science offers a broad high-level training in applied and computational statistics, statistical machine learning, and the fundamental principles of statistical inference. Training is delivered through mathematically demanding lectures and problems classes, hands-on practical sessions in the computer laboratory, report writing and dissertation supervision.
The dissertation component of this course will focus on in-depth quantitative data analyses in an area of your interest, under the interdisciplinary supervision of two academic experts, one from criminology and one from social statistics.