Department of Statistics

Submitted by MIRraf@83na7 on Thu, 04/16/2020 - 14:24
Faculty of Management
Size of the team
number of researchers number of supporting staff number of PhD students
PI name
Mirosław Szreder
PI bio

Professor Mirosław Szreder did his PhD in Economics (mathematical statistics) in 1987. Title of the thesis was: "Subjective Probability Distributions in Bayesian Analysis".

Since 2005 he is full professor in economics.


Professional career:

1980  to  1994

lecturer and senior lecturer in the Department of Statistics, University of Gdansk,

1994  to  1995

associate professor of the University of Gdansk, Faculty of Management,

2006  to  present

Professor, Dean of the Faculty of Management, University of Gdansk (since 2016).

Research interests:

Mathematical Statistics, Bayesian Inference and Decision Making, Sampling Techniques, Business Research, Econometrics.

Teaching experience:

- Lecturer for undergraduates on Theory of Probability, Mathematical Statistics, Business Statistics, Time Series Analysis, at the University of Gdansk.

- Visiting lecturer for undergraduates on Econometrics, Mathematical Statistics, and Sampling, Estimation and Hypothesis Testing in the Department of Economics, University of Leicester, Britain,  in Oct.-Dec. 1989, Jan.-March 1991,  Jan.-March 1994, Jan.-March 1995, and Jan.-March 1996.


Language abilities:

Polish - native, English - fluent, German - sufficient,  Russian – sufficient.

Recent publications (selection):

Szreder M., Will big data affect opinion polls?, “Archives of Data Science, Series A”, KIT Scientific Publishing, Vol. 4, No. 1, 2018.

Szreder M., Gwizdała J.P., Possible future developments of sample surveys in finance. “Argumenta Oeconomica Cracoviensia”, no. 18, 2018, pp. 69-82.

Szreder M., New economy – new challenges for statistics. “Statistics in Transition”, 2012, vol. 13, no. 1, pp. 191-196.

Contact person and e-mail
Contact person
Mirosław Szreder
Contact person e-mail
Short description of research profile

Research areas:

  • multivariate analysis (data classification methods including artificial neural networks, big data),
  • insurance topics (general insurance, life insurance, retirement insurance, health insurance, occupational pension schemes),
  • risk management (general insurance in risk management of small and medium enterprises, applications of survival analysis, logistic regression and scoring method to evaluate insurance risk and risk in socio-economic life),
  • sampling methods (sampling methods in market research, non-random errors in sample surveys),
  • statistical analysis of the labour market,
  • public statistics system.
Research area

Representative publications

1. Wycinka Ewa, Jurkiewicz Tomasz: Survival regression models for single events and competing risks based on pseudo-observations, w: Statistics in Transition, vol. 20, nr 1, 2019, ss. 171-188;
2. Komorowska Olga, Kozłowski Arkadiusz, Słaby Teresa: Comparative analysis of poverty in families with a disabled child and families with non-disabled children in Poland in the years 2014 and 2016, w: Statistics in Transition, vol. 20, nr 3, 2019, ss. 97-117;
3. 4. Migdał-Najman Kamila, Najman Krzysztof, Antonowicz Paweł: Early warning against insolvency of enterprises based on a self-learning artificial neural network of the SOM type, w: Effective investments on capital markets: 10th Capital Market Effective Investments Conference (CMEI 2018) / Tarczyński Waldemar, Nermend Kesra ( red. ), Springer Proceedings in Business and Economics, 2019, ISBN 978-3-030-21273-5, ss. 165-176;
4. Gierusz Anna: Automatic enrolment into occupational pension schemes - the UK model and differences with the proposed Polish program, w: Contemporary problems of intergenerational relations and pension systems: a theoretical and empirical perspective : proceedings of PenCon 2018 Pensions Conference 19-20 April 2018 Lodz, Poland / Chybalski Filip, Marcinkiewicz Edyta ( red. ), 2018, ISBN 978-83-7283-900-8, ss. 153-163;
 5. Szreder M., Gwizdała J.P., Possible future developments of sample surveys in finance. “Argumenta Oeconomica Cracoviensia”, no. 18, 2018, pp. 69-82.  

Link to extended list of publication

Technology Expertise

1. Assessment of sampling schemes used in specific studies and the possibility of inference based on the samples obtained, requested by private entities for which a research company carried out sample marketing research.

2. Analysis of the ISP monitoring project presented by the Innovation Development Department of the Economic Development Department of the Marshal's Office of the Pomeranian Voivodeship based on the industry classification of enterprises; verification and assessment of the quality of the method in terms of usefulness, indication of strengths and weaknesses, opportunities and potential threats.

3. Assessment of methodology used in quantitative research by the Pomeranian Voivodeship (citizens of Ukraine, employers of the voivodeship, population of the voivodeship, unemployed, representatives of social cooperatives, representatives of social integretion centre).