Data Analytics for Business and Economics
Informacje ogólne
| Kod przedmiotu: | 2400-ENSM057B |
| Kod Erasmus / ISCED: |
14.3
|
| Nazwa przedmiotu: | Data Analytics for Business and Economics |
| Jednostka: | Wydział Nauk Ekonomicznych |
| Grupy: |
Seminaria magisterskie dla II roku programów anglojęzycznych |
| Punkty ECTS i inne: |
3.00
|
| Język prowadzenia: | polski |
| Rodzaj przedmiotu: | seminaria magisterskie |
| Skrócony opis: |
This seminar is to support the MA thesis in the data analytics, used in a practice and a theory of business and economics. There are mainly three thematic areas on focus: 1) unsupervised learning methods (k-means, PAM, CLARA, PCA, MDS, association rules etc.), 2) spatial analysis (for geo-located data), 3) Monte Carlo simulation models and bootstrapping. These methods can be addressed in an empirical and as well as theoretical approach. In three semesters time span students are to review the literature, develop own study and complete the thesis. Seminar is conducted as a set of individual regular consultations. |
| Pełny opis: |
This seminar is to support the MA thesis in the data analytics, used in a practice and a theory of business and economics. There are mainly three thematic areas on focus: 1) unsupervised learning methods (k-means, PAM, CLARA, PCA, MDS, association rules etc.), 2) spatial analysis (for geo-located data), 3) Monte Carlo simulation models and bootstrapping. These methods can be addressed in an empirical and as well as theoretical approach. In three semesters time span students are to review the literature, develop own study and complete the thesis. Seminar is conducted as a set of individual regular consultations. Programming is in R. A goal of this seminar is to develop, validate and revise the quantitative methodology and models. Both applied and theoretical works will be supported. Students will refer mainly to current journal literature of the topic. Potential types of thesis: - Comparison of the methods on theoretical and /or empirical data to test similarity and sensitivity of methods, as well as its content capacity - Development of the existing studies by refreshing the results on another datasets and by complementing the conclusions on the results and literature/methodology. - Theoretical features of methods for different datasets, distributions, applications etc. - Case studies for business applications The very desired outcome of the works is a publishable paper. |
| Literatura: |
Selected by tutor for the topic. |
| Efekty uczenia się: |
Students can build the quantitative models, analyse the data and draw the conclusions from the conducted research. Students have a knowledge in R programming and advanced methods of data analysis. Students can design and develop a project by themselves, are dedicated to work and independent on their research path. KW01, KW02, KW03, KU01, KU02, KU03, KK01, KK02, KK03 |
| Metody i kryteria oceniania: |
After first (out of 3) semester students have an outline of the thesis prepared, data is collected and hypothesis is prepared. After second semester (out of 3) literature overview is completed and majority of modelling work done. After third semester (out of 3) thesis is ready for the defense. |
Zajęcia w cyklu "Semestr zimowy 2024/25" (zakończony)
| Okres: | 2024-10-01 - 2025-01-26 |
 
PN WT ŚR CZ PT |
| Typ zajęć: |
Seminarium magisterskie, 30 godzin
|
|
| Koordynatorzy: | Katarzyna Kopczewska | |
| Prowadzący grup: | Katarzyna Kopczewska | |
| Lista studentów: | (nie masz dostępu) | |
| Zaliczenie: |
Przedmiot -
Zaliczenie
Seminarium magisterskie - Zaliczenie |
Zajęcia w cyklu "Semestr zimowy 2025/26" (zakończony)
| Okres: | 2025-10-01 - 2026-01-25 |
PN SEM-MGR
WT ŚR CZ PT |
| Typ zajęć: |
Seminarium magisterskie, 30 godzin
|
|
| Koordynatorzy: | Katarzyna Kopczewska | |
| Prowadzący grup: | Katarzyna Kopczewska | |
| Lista studentów: | (nie masz dostępu) | |
| Zaliczenie: |
Przedmiot -
Zaliczenie
Seminarium magisterskie - Zaliczenie |
|
| Skrócony opis: |
(tylko po angielsku) The seminar focuses on quantitative methods applied to economic and business problems and data. We welcome work using, among others, unsupervised and supervised machine learning and/or spatial modeling and/or Monte Carlo/Bootstrap. The aim of the seminar is for students to prepare a master's thesis, also in the form of a scientific article. As part of their research, students may focus on, for example, customer analysis in relation to sales, purchase history, behavior, preferences, or satisfaction. There are no thematic restrictions in this regard. Papers addressing the issue of space and location are welcome. The work must include quantitative research (econometric, statistical, machine learning, simulation, etc.) on existing or simulated data. Over the course of three semesters, students must familiarize themselves with the literature on the subject, conduct their own research, and write a thesis. The seminar takes the form of a series of individual consultations. |
|
| Pełny opis: |
(tylko po angielsku) The seminar focuses on quantitative methods applied to economic and business problems and data. We welcome work using, among others, unsupervised and supervised machine learning and/or spatial modeling and/or Monte Carlo/Bootstrap. The aim of the seminar is for students to prepare a master's thesis, also in the form of a scientific article. As part of their research, students may focus on, for example, customer analysis in relation to sales, purchase history, behavior, preferences, or satisfaction. There are no thematic restrictions in this regard. Papers addressing the issue of space and location are welcome. The work must include quantitative research (econometric, statistical, machine learning, simulation, etc.) on existing or simulated data. Over the course of three semesters, students must familiarize themselves with the literature on the subject, conduct their own research, and write a thesis. The seminar takes the form of a series of individual consultations. The aim of the seminar is to develop and validate quantitative methodologies and models within the framework of theoretical and practical work. The literature used mainly consists of current scientific publications on the subject. Examples of topics: - determinants, benefits, and costs of investment and location in the industrial sector (e.g., in the automotive industry), - spatial marketing research and market research - spatial real estate valuation - customer segmentation, purchase loyalty modeling, customer satisfaction assessment - sales forecasting - the importance of location and distance in business - spatial differentiation of sales and service provision, market niches - Theoretical aspects of spatial modeling (statistics and spatial econometrics - Comparison of methods based on theoretical and/or empirical data to check the similarity and sensitivity of methods, as well as their predictive power - Development of existing research by refreshing results on other data sets and supplementing conclusions regarding results and literature/methodology. - Theoretical characteristics of methods for different data sets, distributions, applications, etc. - Case studies of business applications Ambitious work in the form of a scientific article is welcome. NOTE: I do not conduct work that involves data collection through surveys. I also do not conduct work related to macroeconomics or international trade. |
|
| Literatura: |
(tylko po angielsku) Papers related to the topic of the thesis Kopczewska, K. (2020). Applied spatial statistics and econometrics: data analysis in R. Routledge. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, No. 1). New York: springer. |
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Właścicielem praw autorskich jest Uniwersytet Warszawski.
