Introduction
Why data analysis?
The power of data and the information therein is entering the heart of almost any section of society. We are discovering that processes can be better understood and controlled, predictions made, causal effects estimated and decisions optimized. Reliable results follow when studies have been appropriately designed, data carefully gathered and analyzed. Scientists and professionals stay ahead if they keep learning from their data. They add tremendously to their market value when data analytic skills merge their subject matter expertise.
Aim
To prepare for ‘big data’ in tomorrow’s world and to face the facts with statistical skills, the Ghent Center for Statistics joins the Institute for Continuing Education of the Faculty of Sciences (ICES) to organize their yearly series of targeted training modules.
We aim to provide insight in the basics of statistical research while developing the technical skills to come to results with statistical software. Blended learning with hands-on sessions on PC’s or laptops allows participants to gain firsthand experience in applying the knowledge.
Target audience
Our courses target professionals and the academically trained, who wish to become confident data analysts, refresh their knowledge or discover new areas of research. The program’s modular architecture facilitates flexible entry and adaptive training trajectories.
Program 2022-2023
The program has a modular architecture to facilitate flexible entry and training trajectories. All modules are planned as on campus courses. However, we live in uncertain times with the corona pandemic still very present in our lives. If the conditions and government and university measures are such that a course cannot take place ‘live’ in all safety it will be offered as an online course instead.
For the 2020-2021 academic year, the program offers basic modules which lay a foundation of statistical knowledge and techniques. We give a basic as well as intermediate course in R, the versatile freeware package that gains ground in all domains. Furthermore we offer a basic courses in Python. New this year is a one day ‘Introduction to NVivo for Qualitative Data Analysis’.
More specialized courses follow: a two-part course on ‘Extensions to the Design and Analysis of Case-Control Studies', ‘Survival Analysis and Competing Risks’, 'Multilevel Analysis for Grouped and Longitudinal Data', 'Machine Learning with Python' and ‘Proteomics’. A course on ‘Propensity Score Methods’ completes this year's program.
Language
All modules are taught in English. Classes take place in a pleasant atmosphere with ample opportunity to interact with the lecturers.
Government support measures
The Flemish Community recognizes the value of lifelong learning for the region’s economic development. Employers are granted financial support through the government’s introduction of the KMO-portfolio. More about this stimulating initiative can be found on the KMO website (in Dutch).
Exam and certificates
Participants who attend classes receive a certificate of attendance at the end of the course. Additionally several modules encompass an exam. Participants who succeed in this test receive a certificate of Ghent University.
Doctoral Schools
Doctoral Schools support young researchers in acquiring the necessary skills. Several modules can, under certain conditions, be incorporated in the program of the Doctoral Schools and are eligible for a refund. To incorporate a course in the Doctoral Training Program (DTP) and to qualify for reimbursement by the UGent Doctoral Schools (DS) it is no longer necessary to take part in the exam but a specific procedure with strict deadlines must be complied with.
Complementary initiatives
Check out the website of the UGent Center for Data Analysis and Statistical Science (DASS) for two more training and consulting services.
Training
Flames, Flanders training network in Methodology and Statistics (www.flames-statistics.eu) is an interuniversity initiative providing further training to young researchers in Ghent and beyond.
Master in Statistical Data Analysis
The one-year UGent advanced Master's program in Statistical Data Analysis leads to a dedicated degree following more intensive training in the methods of practical statistics offered to scientists in diverse areas.
Consulting
The FIRE (Fostering Innovative Research based on Evidence) statistical consulting service offers statistical and methodological support for UGent doctoral students and post-docs during their scientific research. Personalized advice and help is provided during all phases of the research including study design, data collection, statistical analysis, and interpretation and reporting of results.
Book your FIRE consulting slot by filling out the application form at the FIRE website or, contact them for more information.
The IOF valorization consortium Stat-Gent CRESCENDO unites statistical expert knowledge of the Ghent University Center for Statistics aiming to support applied research. It provides consulting services in collaboration with companies, government and other research groups.
Stat-Gent offers an operational framework for statistics and data analysis contract work, in flexible formats including data analysis projects, customized training and software solutions. Data analysis projects add maximum value when the statistical method is integrated in the complete trajectory from objective setting to report writing. Stat-Gent therefore strive for stable and sustained relationships with our partners in mutually rewarding research collaborations.
High-quality work is delivered by well-trained and dedicated statistical consultants, under guidance and supervision of UGent statistics professors.
Stat-Gent has expertise in a broad range of applications, such as (but not limited to)
- design and analysis of clinical trials,
- health economics, epidemiology, electronic health records, quality of care, drug compliance, and evidence-based medicine
- business analytics
- biotech and agriculture,
- statistical genetics/genomics: biomarkers, micro-arrays, dPCR, next-generation sequencing.
Stat-Gent uses a wide variety of statistical methods going from basic regression, analysis of variance, mixed models and multivariate techniques, to more specific methods in causal analysis, data mining, functional data analysis, experimental design, longitudinal analysis, missing data, multiple testing, robust and nonparametric statistics and survival analysis.
Do not hesitate to contact Stat-Gent with questions or for more information.
Wishing you an enjoyable and rewarding learning experience, we look forward to meeting you!