CDA is a center that provides applied, theoretical and simulation based research in statistics, econometrics and data science with specialization in Business Administration, Economics and Finance. CDA has several research collaborations with other institutions as well as with the Swedish industry.
CDA provides (high level) analysis of data (data in a broad context), and particular focus lies on the analysis of Big Data, Prediction, Forecasting, Causality, and the Quality aspects of data. Some simple demonstrations of data analysis (using R and Python) can be found via the Demo link on the left-hand side. This data analysis is enabled by the methods of AI, Machine Learning, Decision Trees, Neural Networks, Random Forrest, Bayesian classifiers, etc.
Teaching is central to CDAs activities, and the students are offered a modern and exciting education in Statistics, Econometrics, and Data Science. Parts of our research is integrated in the teaching, and the practical importance of statistics, econometrics and data science, using authentic examples, is emphasized.
CDA offers a stimulating and exciting research environment, and examples of current research topics are (most of them are part of research projects with external funding):
Forecasting; Business Forecasting; Predictive Analytics; Algorithms for Text and Number Analysis; Consumer Behavior in News Media; Applied and Theoretical Econometrics; Quality of Data; Discrete Events Stochastic Simulation; Measuring Customer Satisfaction, Loyalty and CSR
CDA are also running several research projects (see the link on left-hand side), and has several research collaborations with other institutions as well as with the Swedish industry (including commissioned). CDA seeks continuously for new collaborations and joint projects.
As a research engine for CDA, the Center for Forecasting and Data Analytics (CFDA) is started (see the link on left-hand side). CFDA is a center at the Stockholm School of Economics Institute for Research (SIR).
CDA has an excellent record of research, with publications in journals such as (example publications can be found via the link on left-hand side):
Biometrika; Econometrica; Econometrics Journal; Econometric Reviews; Econometric Theory; Harvard Business Review; Informatica; Issues in Information Systems; International Journal of Forecasting; Journal of Econometrics; Journal of Time Series Analysis; Oxford Bulletin of Economics and Statistics
CDA offers courses to BSc students (at the Business and Economics program and the Retail Management program) where an introduction is given to statistics and econometrics for Business Administration, Economics and Finance. In these courses, the emphasis is on the practical aspects of statistics and econometrics. To facilitate the analysis of models and data, the students are introduced to various statistical software programs (including R). Students will also learn how the estimated models and adherent results can be used as tools for: policy making, investment decisions, prediction, identifying key drivers for customer satisfaction and loyalty, portfolio management, etc.
The CDA also offers more specialized courses at the MSc level, where the students are taught Quantitative Methods for Economic Analysis (using Excel), Applied Time Series Econometrics (using STATA), and Data Science courses (using SQL and R). Courses at the PhD level in Time Series Econometrics (using GAUSS, Matlab, and R) and Quantitative Research Methods and Analysis are also given.
CDA does not have a PhD program of its own. However, it is possible to enroll in a multidisciplinary PhD program in Econometrics/Other Subject in co-operation with some other Departments or Institutions. At the moment CDA has worked out such solutions in co-operation with: Center for Retailing at the Stockholm School of Economics, Karolinska Institutet, Stockholm Business School and Uppsala University. If you are interested in/or have questions about a possible multidiscipline PhD, please contact Rickard Sandberg (email@example.com).
Help with statistical questions and methods in thesis writing
BSc and MSc Students are welcome to get advice on e.g. statistical issues when writing their thesis. At the moment, four faculty members offer their expertise (in a wide range of areas); they are Andreea Enache (firstname.lastname@example.org) Emelie Fröberg (email@example.com), Håkan Lyckeborg (firstname.lastname@example.org), and Rickard Sandberg (email@example.com).
Ask us - we know statistics and how to analyze data!
Need to get in touch with someone who know statistics and the analysis of data? You've come to the right place!
In fact, the CDA is frequently consulted by public and private companies for statistical and data science expertise. If you are interested in such expertise, please contact Rickard Sandberg (email: firstname.lastname@example.org; tel: 08-7369201) and you will be directed to the most suitable researcher.