MaStat Leaflet (1)

7/31/2019 MaStat Leaflet (1)

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Master o Statistical Data Analysis

Dear potential applicant,

It is a pleasure to introduce you to the discipline o statistical science and welcome you to aquick tour o our unique one year postgraduate Master program in Statistical Data Analysisat Ghent University.

With a diploma in (bio-)engineering, psychology, (bio-)medical sciences, economics,educational sciences, you are ready or a promising proessional career. But those oyou with a special aptitude or numbers and the logic o the scientic method may havebecome ascinated with new discoveries that lie hidden in observation, ready or reapingby dedicated, well trained proessionals. Asking the right questions, a targeted gatheringo data and then the extraction o valuable inormation, is becoming an exceedingly

important and rewarding part o proessional as well as scientic lie.

Todays increasing computer power has led to the creation o complex databases inmany domains. Simultaneously, statistical science has developed into a discipline withestablished methods and techniques or a wide range o data structures. Insights obtainedrom appropriate data analysis allow to predict, adjust and optimize processes. On theother hand, inecient or ill structured data collection and analysis can lead to inerior,costly and misguided conclusions with possibly ar-reaching consequences. No wonderthen, that international proessional and research standards in various elds demand highquality data analysis, perormed by well-trained statisticians.

Our Master program oers intensive training by experts in modern statistical methods anddata analysis to scientists rom a wide range o elds, including biology, mathematics, bio-inormatics, genetics, marketing, econometrics, environmetrics, psychometricsIt is designed to sharpen problem-solving skills and build experience in evidence-baseddecision making, to train scientists to become leaders in this eld. It will be the start o lielong learning in an exciting and ast evolving discipline.

Our dedicated teachers have vast practical experience, both locally and internationally, in arange o domains. They oer a truly multi-disciplinary experience. The Centre or Statisticso Ghent University established a research valorisation consortium,Stat-Gent, which osters special relationships with partners inindustry and society and works with their applied problems. Wehope you will be able to enjoy the ull benets o this environmentand look orward to welcoming you as members o our internationalstudent body.

On behal o the curriculum committee,Pro. dr. Els Goetghebeur, chair

Contents

Dear potential applicant ...................................................................3

About the Master training in Statistical Data Analysis ....................4

Structure o the program ..................................................................5

International mobility .......................................................................8

Our students and alumni testiy .......................................................9

As do leaders in health care and nance ........................................11

Why study in Ghent? .........................................................................12

Interested? .........................................................................................15


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About the Master training in Statistical Data Analysis

Aim?

To oer excellent training in the design, analysis and reporting o empirical research.

Who is it or?

The program is open to mature students, who earned a master degree in any eld thatrequired some statistical basis and sucient mathematical background. In September areresher course on Mathematics is oered to brush up basic mathematical skills.

Career perspectives!

Students who successully complete the Master program have acquired an advancedlevel o statistical knowledge and data analytic skills. They are ready to contributeas independent experts to a multidisciplinary team that designs, perorms, analysesand reports on applied scientic research. Our masters are trained to handle practicalproblems in an objective scientic manner and to gain insight into the structure o dataand an underlying model. Computing skills, fexibility, eciency, common sense and anattitude towards continuous learning are important qualities that this program brings.These masters are much sought ater and nd rewarding careers in the pharmaceuticaland other private industries, in banking, research institutions, government, Many oour students also go on to train as PhDs and guide the next generation o statisticalproessionals.

Who is teaching?

The program is oriented towards a wide range o elds o application. It benets roman interdisciplinary team o instructors, experts in statistics with teaching experienceboth locally and internationally at the graduate, postgraduate and proessional level.They oer a truly well connected environment and allow students to acquire moreextensive knowledge in a specic eld o their choice such as biostatistics, behaviouralsciences, economics or biotechnology-genetics.

Structure o the program

The program consists o ve mandatory courses, our elective courses and a masterdissertation. Three elective courses are chosen rom a predened list. Throughout theprogram, lectures are supported by project work and take home assignments, which helpdevelop skills o practical data analysis and provide experience with real data handling.The program can be taken as a one year full- time program or it can be spread overtwo or more years. Many courses are taught in the evening to acilitate work and studycombinations.

The precise sequence o oered courses may vary rom year to year. We reer to ourwebsite http://www.mastat.ugent.beor the latest inormation. In a typical year, ourmandatory courses are taught in the rst semester. The program starts with Principles ofStatistical Data Analysis, which provides a solid background in basic statistical concepts andtechniques, rom a theoretical as well as practical perspective. It sets the tone or rigorouswork and in depth understanding in a practical context. This course takes place in the rsthal o the semester. We build on it when developing models or a univariate outcomein the coursesAnalysis of Continuous Data and Categorical Data Analysis. The course onStatistical Computing runs through the entire semester and provides necessary skills towork with databases and statistical sotware, concentrating on SAS and R. In addition, asmall number o elective courses are oered in the rst semester. Full time students andpart time students in their last year decide on the specic problem they wish to solve intheir master thesis. As ar as a possible topic goes, the sky is the limit. Proessors proposea range o topics each year, but students are also encouraged to bring their own problemor data. Collaboration with proessionals and researchers adds extra value to this process.During the rst semester, students start exploring the relevant literature and choose athesis supervisor under whose close tutorship they will work towards a solution.

The second semester includes the mandatory course onStatistical Inference, which providesa more general and unied methodological basis or the statistical design and analysiso empirical studies. The majority o elective courses are urther oered in this semester,

or instance Causality and Missing Data, Experimental Design, Longitudinal Data Analysis,and Monte Carlo and Computer Intensive Methods in Statistics. The course Capita Selectapresents a dierent subject each year and may be taught by visiting aculty, specialized ina particularly exciting topic. While we believe the program in Ghent is very attractive, wealso encourage students to discover the world and possibly take one or more courses ina European program o high quality. We are or instance partners in a Nordic BiostatisticsMaster Course Network. Students in their nal year may nish their master dissertationin this semester and report both orally and in writing about the problem studied, theapproach taken, and the results obtained. Close mentoring during the thesis processprovides students with the unique opportunity to learn rst hand rom an experiencedstatistician how the statistical method gets applied to solve real world problems.


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An overview of typical courses and their workload according to the number of credits(ECTS = European Credit Transfer System) follows for quick reference:

Mandatory courses:

Theory Practice ECTS

Principles of Statistical Data Analysis 22.5 40 5

Statistical Computing 22.5 40 5

Analysis of Continuous Data 22.5 40 5

Categorical Data Analysis 22.5 40 5

Statistical Inference 30 15 5

Master Dissertation 15

A list o elective courses:

Analysis of Univariate Time Series 22.5 40 5

Capita Selecta 22.5 40 5

Causality and Missing Data 22.5 40 5

Computational Biology 22.5 40 5

Data Mining 22.5 40 5

Epidemiology 30 30 5

Experimental Design 22.5 40 5

Longitudinal Data Analysis 22.5 40 5

Monte Carlo and Computer IntensiveMethods in Statistics

15 40 5

Multivariate Data Analysis 22.5 40 5

Spatial Statistics 30 30 5

Survival Analysis 22.5 40 5

Elective courses have to be chosen or a total o 20 credit points a minimum o three courses are chosen rom the list above,

the nal course can come rom any study program at Ghent University or other institutions o higher education, subject

to the acultys approval. Students wishing to spend (part o) the second semester abroad are encouraged to explore the

possibilities.

For more details and the latest inormation on program contents and lecturers, pleasesee the program section o our website, http://www.mastat.ugent.be

For students with a specic ocus, we recommend trajectories o elective courses, corresponding to modules Biotechnology-

genetics, Biostatistics, Economics and Behavioural Sciences. The order in which the courses appear in each module below

indicates the recommended order in which part-time students may take these courses

Master Dissertation

StatisticalComputing

Prinicples of Statistical Data Analysis

Statistical InferenceAnalysis of Continuous Data

Categorical Data Analysis

Biostatistics

Multivariate Data AnLongitudinal Data AnSurvival AnalysisEpidem or Causality

Economics

Multivariate Data AnAn of Univar Time SeriesDate MiningCausality or...

...

...

...

...

Behavioural Sciences

Multivariate Data AnLongitudinal Data AnSurvival AnalysisCausality

Biotech-genetics

Multivariate Data AnComputat. BiologyData MiningExperim. Design


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International mobility

Our program is anchored in an international environment o research and education.We encourage exchange o lecturers and students. The international dimension o thetraining shows up in many ways:

International experts are invited to teach specialized courses.

Our own lecturers teach regularly at international institutes.

The English program draws a rich group o oreign students.

We participate in a network o statistical master programs which involves theuniversities o Stockholm, Oslo, Helsinki, Copenhagen and Newcastle. Students areoered the opportunity to ollow a course in one o the collaborating universities.

Credits earned or equivalent subjects may be recognized between dierentinstitutes.

Below are some excerpts o what (ormer) students as well as leaders in the feldwished to say about how they value this program and statistical data analysismore generally.

Full testimonies and more can be ound on our website:

http://www.mastat.ugent.be.

Our students and alumni testiy

David Mwakazanga, Degree in Demography and Statistics, was Trainee Data Analyst,Tropical Diseases Research Centre, Zambia:

As a student who spent a considerable time searching the world or a statisticalprogram that would suit my personal and job requirements and a scholarship, I thinkits essential that the Master is oered as a one year ull-time program. The contentis fexible enough to accommodate career needs and all sorts o student backgrounds.[] Additionally, potential scholarship unds are not very willing to sponsor a studentor more than a year to get a master qualication.

Karel Spitaels, Civil Engineer, at `Transport & Mobility Leuven:

Beore attending the Master program, I studied civil engineering. There I gained a

great deal o theoretical knowledge, but little experience with practical application. TheMaster program developed my skills and insight in model building, in the meaning odata and in causality, making me much more versatile as a researcher and teaching mehow to put theory into practice. I now work at the research rm Transport & MobilityLeuven, where I am responsible or data preparation, statistical data-analysis andmodel building.


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Katrien Verschueren, Bio-engineer, at Ablynx (biopharmaceutical company, Ghent):

I have spread the Master over two years as I combined it with a ull-time workassignment. It was a tough combination; however a very interesting balance betweentheory (in class) and practice (at work). [] Most importantly the Master programdelivered the undamental basics to understand the concepts and at the same time thetools and the inormation about how to tackle everyday statistical problems encounteredat work.

Marijke Welvaert, Master in psychology, teaching assistant and PhD student inPsychology, Ghent University:

During the Master a whole new exciting world opened up and slowly I became part oit. [] The skills and knowledge I achieved in the Master help me now to anticipate theproblems that my students have and make it a lot easier to explain what statistics areabout. [] But not only in teaching I can rely on the Master, also or my PhD the practiceI received will be indispensable.

Mieke Van Hemelrijck, Master in Biomedical Sciences (UGent) and International Health(Harvard School of Public Health), PhD student Epidemiology, Kings College London:

This year o statistical theories, programming, analyses, and applications was a hugechallenge or me. [] Nevertheless, I enjoyed it very much as it was an excellentopportunity to learn rom classmates and proessors rom across the University applyingstatistics in dierent elds. [] The Master degree in Statistical Data Analysis providedme with much practical statistical knowledge, which has helped me throughout thecourse o my studies in Public Health.

as do leaders in health care and nance.

Pro. Dr. Marleen Temmerman, Department of Obstetrics and Gynaecology, GhentUniversity; Director International Centre for Reproductive Health:

Appropriate and reliable data are much-needed or anyone involved in health care,whether at the level o planning, execution, research or practical implementation.Within the ramework o clinical and operational research, the importance o a thoroughexperimental design, accurate data collection and a proessional statistical analysiscannot be stressed enough. [] Especially in international research the quality oinormation is extremely important, and this requires knowledge which we as doctorsdo not suciently have. For this reason, I took a course in epidemiology and statistics,in order to understand the basics and to be able to think in a moregoal-oriented manner with regard to certain research questions.But what this course especially made me realize, is how importantthe role o a proessional statistician can be. Since then, in allour projects, whether epidemiological, clinical, sociological or inthe laboratory, we cooperate with statisticians, preerably withknowledge o and interest in health. [] I am convinced that thisMaster gives an answer to an enormous need rom eld workers,where the important health problems cry out or a well-consideredevidence-based approach.

Pro. Dr. Herman Verwilst,Chairman of the Board of Directors of Fortis Bank:

Data analysis orms, and has always ormed, one o the most prominent activitieswithin the nancial sector and its development has been an important actor in theexpansion o nancial institutions. [] The recent directives o the Basel Committeeaim or a more economic approach o the various nancial risks, in particular the

counterparty risks. A parallel policy applies in the insurance worldwhere Solvency II clearly also opts or the more economic point oview. This new regulation not surprisingly works as a catalyst orchange in many elds, and data analysis is one o these. Indeed,statistics is a science which is heavily called upon in this context.As some examples we cite a number o traditional methods:linear and logistic regression, discriminant analysis, decision trees.More advanced technologies are also making their way up (kernelmethods) and are usually combined with other procedures suchas descriptive analysis, sampling and simulation (Monte Carlo).


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Why study in Ghent?

Ghent, a crossroad o statistical activity

Historically. The study o statistics at Ghent University has a longhistory. Indeed, the very rst doctorate that was completed atthis university was that o the amous Adolphe Quetelet (1796-1864). His more than 300 scientic publications refect the manycontributions he made to the discipline o statistics. He wasespecially infuential in two areas: the introduction o the concepto the average man (lhomme moyen), and the work arounddierent statistical distributions

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.

Today. Ghent University is one o the most important institutions o higher education andresearch in the Low Countries. The university yearly attracts over 30,000 students, with aoreign student population o over 2,200 EU and non-EU citizens. The Center or Statisticso Ghent University covers a critical mass o statistical experts rom various scienticdomains. Its members are at the oreront, nationally and internationally, in research,education and consulting. They are experienced in practically oriented postgraduateteaching through the continuing education o PhD students, academic researchers andproessionals rom outside the university. More inormation about the members andactivities o the Center or Statistics can be ound on http://www.cvstat.ugent.be

Ghent, sparkling city

Ghent prides itsel in a rich history. In medieval times, particularly during the 11th and12th century, the city became a prominent trade centre in North-West-Europe. Charles V,one o Europes great rulers, was born here in the year 1500. Later the city sueredrom religious troubles, like most cities in the Low Countries, but rom 1800 on, peaceand prosperity were restored thanks to new actories such as the successul cotton mills.The 19th century brought continuing industrial growth and the number o inhabitantsexploded.

Today, Ghent is a fourishing, lively cultural city, with a riendly atmosphere, a diversepopulation and ascinating architecture. It is also home to many students, makingup a considerable part o the 250,000 inhabitants, who give the city an ever-youngcharacter.

1) For more details we reer to Stigler (1986), The History o Statistics, p.161-220, Harvard University Press, Cambridge.


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Interested?

With specic questions, you are welcome in the various aculties:

Medicine and Health Sciences:Prof.Dr.GeorgesVanMaele(tel09/[email protected])

Bioscience Engineering:Prof.Dr.OlivierThas(tel09/[email protected])

Economics and Business Administration:Prof.Dr.DirkVandenPoel(tel09/[email protected])

Engineering:Prof.Dr.RenBoel(tel09/[email protected])

Political and Social Sciences:Prof.Dr.RonanVanRossem(tel09/[email protected])

Psychology & Educational Sciences:Prof.Dr.YvesRosseel(tel09/[email protected])

Sciences:Prof.Dr.ElsGoetghebeur(tel09/[email protected])Prof.Dr.StijnVansteelandt(tel09/[email protected])

University colleges (Hogescholen):Prof.Dr.PatrickCalders(tel09/[email protected])

Veterinary Medicine:Prof.Dr.LucDuchateau(tel09/[email protected])

Further up-to-date inormation, instructions or enrolment and pointers to grants andscholarships, are available on the website o the Master o Statistical Data Analysis:http://www.mastat.ugent.be


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http://www.mastat.ugent.be - http://www.cvstat.ugent.be

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MaStat Leaflet (1)