EGC | Master SDA Master of Statistical Data Analysis (SDA)Motivation
Career PerspectivesStudents who successfully finish the master program have acquired an advanced level of statistical knowledge and data analytical skills. This will allow them to work as an independent expert within a multidisciplinary team that designs, performs, analyses and reports about applied scientific research. Photo Our masters are trained to handle practical problems in an objective scientific manner and to obtain insight in the structure of data and the underlying model. Given the continuing evolution in statistics and science in general, our masters have been encouraged to think critically and be creative problem solvers. They are stimulated to continuously extend their knowledge and insights. Computational skills, flexibility, efficiency and an attitude towards continuous learning are important qualities that this program brings to its masters to prepare them for a successful career. The program is oriented towards a wide range of fields of application which is guaranteed by the interfacultary team of teachers, leading to a multidisciplinary approach. The elective courses allow students to acquire a more extensive expertise in a specific field of study such as biostatistics, behavioral sciences, economics or biotechnology-genetics. Programme's StructureThe program offers a profound training in design, analysis and reporting of empirical research. It is open for all students with a Master's degree that have had a basic statistical training and have sufficient mathematical background. In September a refresher course on Mathematics is offered to brush up your mathematical skills. The program consists of five mandatory courses, four elective courses and a master dissertation. Three elective courses are chosen from a predefined list. In every course, the development of theory is supported by projects and assignments which help develop skills of practical data analysis and provide hands on experience with real data. The program can be taken as a one year full time program or it can be spread over two or more years. Several courses are taught in the evening. Four mandatory courses are offered in the first semester. The program starts with "Principals of Statistical Data Analysis" which provides a solid background in basic statistical concepts and techniques, both from a theoretical and practical perspective. This course takes place in the first half of the semester. In the second part of the semester, statistical knowledge and data analytical skills are further developed and applied to models with a univariate outcome in the courses "Analysis of Continuous Data" and "Categorical Data Analysis". The course "Statistical Computing" provides the skills that are necessary to work with databases and statistical software. The focus is on the statistical programs SAS and R. Besides the mandatory courses, four elective courses are offered in the first semester. These courses focus on specific data types and data structures. They build upon the contents of the mandatory courses. The elective courses in the first semester are "Multivariate Data Analysis", "Spatial Statistics", and "Survival Analysis". Full time students and part time students in their last year also start exploring literature relevant for their master dissertation, in which they will solve a practical statistical problem in an interdisciplinary context. The second semester contains the mandatory course "Statistical Inference" that provides the general methodological basis for statistical design and analysis of empirical studies. Additionally, several elective courses are offered in this semester: "Analysis of Univariate Time Series", "Capita Selecta", "Causality and Missing Data", "Computational Biology", "Data Mining", "Epidemiology", "Experimental Design", "Longitudinal Data Analysis", and "Monte Carlo and Computer Intensive Methods in Statistics". The topic of the course "Capita Selecta" varies yearly and is taught by a visiting expert on the subject. Students in their final year also finish their master dissertation and report their solution and results both orally and in writing. The master dissertation allows the student to show that he/she can correctly apply statistical knowledge and skills to a practical problem, which is an important aspect of the program.Master Chair
InstitutionGhent University (UGent, Belgium)
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Increasing computer power and the professional need to extract objective information from collected data have lead to complex databases. Simultaneously, statistical science has become a large discipline with well developed methods and techniques for a wide range of data structures. Knowledge obtained from correctly analyzed data allows to predict, adjust and even optimize processes based on empirical evidence. On the other hand, inefficient or incorrect data collection and analysis can lead to inferior or misleading conclusions with possibly far-reaching consequences. Therefore, the international professional and research standards in various fields demand high quality data analysis, performed by well trained statisticians. This program offers training in modern statistical methodology and data analysis to scientists from a wide variety of fields including biology, bio-informatics, economy and marketing, environmental and life sciences, engineering, mathematics and physics, psychology and social sciences … . This complementary training enables scientists to play an important role within their discipline.
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