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What is the most pythonic way to run an OLS regression (or any machine learning algorithm more generally) on data in a pandas data frame? python pandas scikit-learn regression statsmodels share | improve this question. Linear Regression using Pandas (Python) November 11, August 27, John Stamford General So linear regression seem to be a nice place to start which should lead nicely on to logistic regression.
However, as with anything else generalization usually sacrifices performance. So if you focus on one feature for your application you may be able to create a faster specialized tool. Note This documentation assumes general familiarity with NumPy. DataFrame Attributes and underlying data pandas. Panel Attributes and underlying data pandas.
IndexSlice MultiIndex Constructors pandas. Hiermit sollen die Studierenden die aktuellen Entwicklungen im nationalen und internationalen Wettbewerb selbständig beurteilen lernen. Wozu kann Industrieökonomie genutzt werden? Theorie der Unternehmung III. Ausübung von Monopolmacht IV. Oligopole und strategische Entscheidungen. Tirole, Jean, Industrieökonomik, R. Bester, Helmut, Theorie der Industrieökonomik, Springer, Gute mikroökonomische und spieltheoretische Kenntnisse sind vorteilhaft.
Ursachen für Marktmacht Preisstrategien Marktsegmentierung Wettbewerbspolitik. Belleflamme, Paul; Peitz, Martin: Markets and Strategies, Cambridge University Press, International Aspects of Environmental Economics. Sommersemester , Sommersemester Die Studierenden kennen und verstehen - Grundlegende Zusammenhänge zwischen Ökonomie und Ökologie, - Ökonomische Methoden der Bewertung von umweltpolitischen Eingriffen, - Wirkung von Umweltpolitik in offenen Volkswirtschaften, - Entstehungsbedingungen von internationalen Umweltabkommen.
Sie erwerben die Fähigkeiten - Grundlegende Befähigung zur umweltökonomischen Politikberatung, wie z. Erfolgreiche Teilnahme an der Klausur 90 min sowie schriftliche Bearbeitung von Pflichtaufgaben. Vertiefung des Verständnisses für Fragestellungen der internationalen Beziehungen sowie strategisches Verhalten in Verhandlungen.
Vorlesung, Übung, Seminar, Projektarbeit. International Environmental Agreements R-Module. Teilnahme am Kurs "Internationale Umweltverträge" im 1. Erfolgreiche Anfertigung zweier Zusammenfassungen der einschlägigen Fachliteratur sowie deren Präsentation. Vertiefung des Verständnisses für Fragestellungen der internationalen Beziehungen sowie des strategeschischen Verhaltens in Verhandlungen zu Umweltproblemen. Aufarbeitung aktueller wissenschaftlicher Literatur zum Thema "Internationale Umweltverträge".
First come, first served. Knowledge in micro- and macroeconomics, math and statistics. A refresher of the macroeconomic models of the open economy will be provided in the exercise classes. We will analyze micro- and macroeconomic models to understand speculative dynamics on financial markets and stability of financial markets.
We will start with analyzing the impact of the different groups of financial investors on asset prices. Afterwards various kinds of financial crisis including banking, currency and sovereign debt crises will be examined.
We will also discuss the policy implications and policy tools crisis to avoid such crises. Participants should deal with scientific literature and should present one paper in the exercise class. The basis for financial and currency crises? Globalization of the financial markets 3. Currency crisis models 5. Models of currency crises. Währungs- und Finanzkrisen Taschenbuch ; Vahlen, 1. Auflage Bikhchandani, S. Learning from the Behaviour of Others: Conformity, Fads, and Informational Cascades, in: Journal of Economic Perspectives, Vol.
The role of expectations; in: American Economic Review, Vol. Exchange rates and international finance; Prentice Hall, Halow, 4. Journal of Finance, Vol. Bank runs, deposit insurance, and liquidity; in: Journal of Political Economy Vol. Herd on the Street: The Journal of Finance, Vol. Information, trade and common knowledge, in: Journal of Economic Theory, Vol. To register for the seminar you have to send an E-Mail to Boeing europa-uni. Students should have the skills to discuss macroeconomic shocks in models of the closed and open economy in a graphical, verbal, and formal way.
Students should be able to run and interpret OLS regressions. The essay is due on February 28, Both tasks can be done in groups of two students.
All students have to actively participate when a group has to present its solution. After successfully completing the course, students should be able to: Demonstrate knowledge about the models of international macroeconomics: Have a good understanding of the models of international macroeconomics and their implications.
Have a good understanding of the assumptions characterizing each model and be able to compare models on the basis of these assumptions. Analyze complex micro and macroeconomic problems by applying several theoretical or empirical methods. Should have the skills to conclude about appropriate policy response in the different settings. Demonstrate competences that enable students to: Apply their knowledge to other contexts, like news from the media, figures released in the press or in the statistics.
Describe and explain their solution of case studies in a written or oral way. An alternative framework, the BMW model, has been proposed by Bofinger et al. The BMW model is able to discuss more recent concepts of monetary policy such as interest rate rules and inflation targeting. Based on this model, many different macroeconomic questions can be analyzed.
In the essay and presentation students should analyze and discuss a macroeconomic topic based on the BMW model and on additional literature. The specific topic for the essay and the presentation can be chosen in the first weeks of the course. A new framework for teaching monetary macroeconomics in closed and open economies, Würzburg economic papers, No. Is there a core of practical macroeconomics that we should all believe?
American Economic Review, Papers and Proceedings, — The program LaTeX has to be used for all written papers as well as presentations. All solutions have to follow the structure of a scientific paper: Front page, table of contents, list of figures, list of tables, list of abbreviations, variables, indices. All equations have to be numbered consecutively.
References as usual and a list of references in the end of a paper. Students have to follow the usual rules with respect to academic honesty. Especially, we expect that students do not use any material Solutions from previous classes, papers written for different classes without referencing appropriately.
As a prerequisite you need knowledge in microeconomics, macroeconomics, international macroeconomics, math and statistics Bachelor level. You have to register by sending an E-Mail to Dunsch europa-uni. The capacity is limited to 25 students. The purpose of the course is to introduce the students to some of the most widely used models in monetary theory which built the basis for the monetary policy.
The course provides basic tools for performing comparative static and dynamic analysis by relying on models for the closed and open economy. This tool-box contains verbal, graphical and mathematical tools. In addition, the students get hands-on experience analyzing economic data by using Excel or an econometric software.
In relation to the study program's qualification profile, the subject explicitly focuses on: Gain knowledge about the different theories that explain the factors which affect money demand or money supply.
Students possess the skills to analyze, compare and evaluate the consequences of various macroeconomic shocks on a small open economy. They also gain the skills to quantify these effects. To be more specific, students acquire the skills to apply, for example, Cramer's rule to solve a linear system of equations.
Enhancing skills in application of statistical procedures to test hypotheses generated by the theoretical models. The students master the scientific methodologies of a univariate regression analysis, which includes hypothesis testing and confidence intervals. These regressions might be of time series or cross-section regressions type.
Panel econometric techniques are not applied. For example, we rely on regression analysis to derive the optimal weights of a Taylor rule for monetary policy. In the monetary policy part, students gain knowledge about the strategy, the objective, and the various instruments of the ECB. We will clearly differentiate the two phases before and after crisis to understand the breaks in monetary policy. We will always try to refer to the theory part when analysing the consequences of, for example, quantitative easing for the economy in the short and long run.
Students acquire the competence to manage work and master situations that are complex, unpredictable and require new solutions. This competence is practiced in 3 group assignments which should be solved in a group of students. Group assignments train the competence to initiate and implement research activities within a professional cooperation and take on professional responsibility. The results of the weekly assignments are presented by one group of students to train the skills to present and communicate research based knowledge in a professional manner.
Subsequent class discussions train the communication competencies of the group as well as their classmates. In order to strengthen the competencies to independently take responsibility for own professional development and specialization a written exam is also a part of the overall grade.
This will also strengthen the skills to structure economic thinking and to communicate with professionals and non-specialists in a written form. What do we know already? Demand for money 3. Money supply process 4. Monetary policy transmission 5. Rules versus discretion 6. Strategies simple rules for a stability oriented monetary policy 7. Monetary policy of the ECB before and after crisis.
Monetary Policy Oxford University Press Students should have the skills to discuss macroeconomic shocks in models of the closed or open economy in a graphical, verbal, and formal way.
They have some knowledge about the effectiveness of monetary and fiscal policy in macro models of the open economy under fixed and flexible exchange rate regimes. The mathematical knowledge of function optimization with or without constraints constitutes therefore an asset.
Components and their weights: The final grade is calculated by the weighted average of all single components. To achieve credits as T-module 7 ECTS Credits , one short essay pass-fail has to be done additionally as group work of two students.
Please notify us until April 30th, , if you would like to use this option. Demonstrate knowledge about the models of international trade: Demonstrate skills that enable students to Apply their knowledge to the reading and analysis of journal articles in the literature covered.
Demonstrate competences that enables students to: Afterwards, we will use the Blanchard et al. We will also look at the material discussion papers conference videos speeches provided on the webpages of the Institute for New Economic Thinking http: One main focus will be the financial crisis including banking, currency and sovereign debt crises. We will also discuss the policy implications and policy tools to avoid such crises.
Lecture, Exercise, Group Discussions. This is a reading class! You have to come to class well prepared! June 6, Congressional Research Service , www. Taxes versus Spending, in Tax Policy and the Economy, ed.
University of Chicago Press, , pp. In order to facilitate the exchange of thoughts all students are expected to use name tags. In order to document the attendance pattern of the class members, a signature list will be passed around at the beginning of each lecture. Seminar in International Economics R-Module. Teilnahme an einer einschlägigen Veranstaltung zuvor, siehe Seminarankündigung. Erfolgreiche Anfertigung einer Seminararbeit unter Berücksichtigung der einschlägigen Fachliteratur sowie eine mündliche Präsentation der Seminararbeit.
Vertiefung der Anwendung vor allem mikroökonomischer Methoden auf den Themenkomplex, Erlernen des Umgangs mit Fachliteratur, Verbesserung der eigenen Ausdrucksmöglichkeiten.
Wirtschaftliche Analyse globaler Zusammenhänge mit Hilfe von empirischen oder theoretischen Methoden. Wird in der Einführungsveranstaltung besprochen. The subject of environmetrics is the statistical analysis of environmental processes.
Environmetrics has close relationships with many other fields of science like natural sciences, engineering, medicine and economics. As environmental issues become more complex and environmental decision-making strives to be more precise, quantitative analysis becomes more important. New questions are requiring the development of new statistical methods and quantitative techniques to provide answers.
The students should get familiar with statistical methods that are used to analyze environmental data and learn how these methods can be successfully applied to environmental data. Besides that, a short revision of multiple linear regression theory and both a theoretical and practical introduction to Geostatistics will be provided. Moreover, other important information concerning seminar papers and presentations will be mentioned during the first meeting.
El-Shaarawi and Walter W. A unified strategy for building simple air quality indices. Recovering information from synthetic air quality indexes.
Atmospheric Environment, 42, Aitana Lertxundi-Manterola and Marc Saez Modelling of nitrogen dioxide NO2 and fine particle matter PM10 air pollution in the metropolitan areas of Barcelona and Bilbao, Spain. Modelling emission of road traffic from a tunnel study. Zwiers and Hans von Storch On the role of statistics in climate research. International Journal of climatology, 24, Gabriela Beblo and Wolfgang Schmid: January , Europa-Universität Viadrina: Allcroft A spatiotemporal auto-regressive moving average model for solar radiation.
Journal of the Royal Statistical Society, 57, Strategic Trade Policy Seminar. Helpman, Elhanan; Krugman, Paul: Compatible aid and recovery. The lectures will be scheduled mid of November Further information can be found in Moodle. Cambridge University Press, Lyons: Details zur Lehrplanung auf der Lehrstuhl-Webseite.
Solide Kenntnisse in mikroökonomischen Methoden sind von Vorteil. Anwendung vor allem mikroökonomischer Methoden auf den konkreten Komplex Migration, Erlernen des Umgangs mit Fachliteratur. Dieser Kurs untersucht die wirtschaftlichen Auswirkungen der räumlichen Mobilität von Individuen und Haushalten.
Aufbauend auf einer Analyse der einzelwirtschaftlichen Motive für Migration werden die Effekte internationaler Wanderungsbewegungen aus Perspektive der Weltwirtschaft und der betroffenen Nationalstaaten diskutiert. Hinsichtlich der politischen Anwendung steht die Migration von und nach Europa, die Migrationspolitik der EU und einzelner Mitgliedsstaaten im Vordergrund.
Ausführliche Informationen zu den Inhalten der Veranstaltung finden sich auf der Homepage des Dozenten. Both theory and practice are combined in the program, taking into account that both parts are needed as a sound foundation for a successful business career. In this way our graduates are well prepared for the challenges they will be facing in their professional careers.
Well-known CEOs have followed this path. On the way up the ladder, typical positions IOM graduates can expect to fill are project or program manager, logistics manager, systems analyst, IT application specialist, or consultant in key areas like ERP enterprise resource planning and SCM supply chain management. Written exam 90 min. Students are able to derive relevant business knowledge through methods of Intelligent Data Analysis from large, complex databases.
They know and are able to adapt and implement process models of intelligent data analysis for decision support of business problems. Based on the business problem at hand, students can select and apply the appropriate data analysis models, data mining methods and algorithms and derive plans of actions to improve the business problem. Students also have basic knowledge on fundamentals of simulation systems and know several fields of application for simulation systems.
This course consists of two parts. Guide to Intelligent Data Analysis, Springer. Experience in programming is not necessary. Submission of the home programming assignments, implementation of a working data analysis solution and its presentation.
The participants learn basic programming concepts on the example of Python language in a data analysis framework. Python is one of the most demanded programming languages in scientific research and on highly-qualified jobs in industry. The course consists of two milestone blocks: The first block is closer to the standard class: During this part student will get to know about programming, Python language, its state-of-the-art capabilities in data analysis including the overview of data analysis theory.
Outline of the 1st block: Decision and Control Structures 3. Data Storage and Processing 5. Statistics, Plotting and Visualization 6. Getting Data from the Internet In the second block students receive analysis cases with clearly defined research aims.
In compact groups they have to develop a solution using received knowledge and perform data analysis. Students will acquire the capability to develop in teams, apply special analysis techniques and select appropriate programming methods to solve the business tasks.
Lectures in programming are accompanied by tutorials and homework assignments. As a student you are expected to solve the exercises given home. Students will work in small groups to develop, implement and present working solutions of data analysis.
A Bite of Python. An Introduction to Computer Science, 2nd Ed. Data Science from Scratch: Python for Data Analysis: Simultaneous or previous participation in the track modules "Operations Research" or "Management Science", good knowledge and deep interest in mathematical modeling and quantitative methods.
Successful written exam min , bonus point from exercise sheets. The participants will learn how to build model-based decision support systems for making and planning business decisions under uncertainty and risk. Many managerial planning and decision problems are characterized by uncertainty and risk. In this lecture, we will introduce the two most important approaches in this respect, namely stochastic programming and robust optimization, from a modeling and systems point of view.
Also, we want to get acquainted with modelling languages for stochastic optimization and learn how to implement small illustrative applications ourselves. Lectures, exercises, hands-on work, self-studies. Introduction to Stochastic Programming. Modeling with Stochastic Programming. Lectures on Stochastic Programming. Princeton Series in Applied Mathematics. Additional topic specific and proprietary material. The aim of the course is to provide skills and knowledge that will help students to understand the main business processes in an enterprise and to give them guidance on how to use information systems to support the particular business processes.
Enterprise resource planning ERP and supply-chain management SCM are the most important approaches to planning and controlling in enterprises that produce and sell products. While ERP systems are the backbone of information processing in any industry today i. This is increasingly important in today's globally networked economies where supply chains extend across countries and continents. Textbook course, weekly tests, exercises, hands-on work. Bonus system in effect will be explained in the first lecture.
Each summer semester; last time summer semester Successful completion of the exam 90 min and successful preparation of a term paper worth 12 pages as well as presentation of the results of work. Information management is the conscious process by which information is gathered and used to assist in decision making at all levels of an organization. It is inherently interdisciplinary, requiring aspects of economics, management, law, and ethics. Information management has become a powerful resource and a large expense for many organizations that significantly contributes to the overall success of the business.
The course covers various aspects of managing information within an organization, including the organization of and control over the structure, processing and delivery of information.
The different phases of the life cycle of information, like the origin, allocation, evaluation, dissemination, and consumption, are analysed from the business point of view. Using concepts and methods presented in the course, the participants should understand how to organize information and be able to analyze user information needs in order to provide and assure the quality and value of information to decision makers.
Managing Information in Modern Organizations 2. Information as an Organizational Resource 3. Information Management Strategy 4. Lecture, group work, Harvard Business School case studies, presentations. Achim Koberstein until summer semester Understanding of business information systems development. The basic question we will answer in this course is: How can an organization today obtain the information systems it needs? What does it take to ensure that those systems are of a good quality and that they work together properly, supporting the needs of the organization?
Developing information systems started as a mainly technical activity and today has evolved into an activity with strong management involvement. Managerial-level decisions are required throughout the entire process. Both technology and business perspectives are covered in this course. Information systems in the enterprise 2. Information systems architectures and platforms 3.
The management of making information systems 4. Analysis, design, implementation, and testing issues 6. Buying and customizing information systems 7. Project management and tool support. Lectures, excercises, hands-on work. Should be attended simultaneously or after the module "Information Management". Successful preparation of a term paper worth 20 pages as well as presentation of the results of work.
Information plays a key role in management. Managers routinely need to find information on unfamiliar issues, topics or markets to make decisions. Locating this information may require research into unknown and uncertain areas. And there is no one best method to locate such information. In this exercise students will be able to explore different methods for gathering and analyzing of information. Group work, use of practical examples, presentations, discussions.
Students will get to know fundamentals of informations systems for transportation applications. They will achieve an overview on architectures of information systems strategic, tactical, operational , their technological fundamentals, and they will get to know typical business task in transportation and how decision making can be supported through information systems.
The course consists of two parts: We will cover the following topics: Information Systems for Transportation Data Collection for Traffic and Transportation Systems Required Technology Location Planning Travelling Salesman Problem Vehicle Routing Problem Note that there will be an R-Module within the 2nd block, where the theoretical background of this class is applied by students through implementation of discussed algorithms. Class presentation and discussion.
Will be discussed in class. It will be mandatory for participants to have passed the previous lecture successfully. The course is limited to 16 participants. Application via Moodle is required. The core topic of the R-Module will be the development and improvement of rack-based Bike Sharing Systems. In recent years, Bike Sharing Systems have evolved all over the planet, and they often have become an environmental-friendly alternative of urban mobility on the edge of personal and public transportation.
Students will work in groups to analyze operational data from different, existing bike sharing systems, embed them in geographical information systems, and create examples for optimization problems and solutions discussed in the lecture.
Wednesday, June 7, Wednesday, June 28, Wednesday, July 19, , HG If you cannot make it to one of these dates, the module is not for you. Presentation, discussion, data analysis, modeling and solving optimization problems. Bike Sharing Data Analysis. Einreichung von Bewerbungsunterlagen CV, Notenspiegel, usw. Genaue Informationen werden separat bekannt gegeben. Aktive Teilnahme an dem entsprechenden Projektseminar. Die Studentinnen und Studenten sollen Theorien, Modelle und Verfahren nicht nur kennen und verstehen lernen, sondern auch Wissen darüber erwerben, wie diese in die praktische Diskussion eingebracht und eigene Positionen erarbeitet werden können.
Ziel ist es, die verschiedenen Problemstellungen zu erkennen, zu analysieren und zu lösen. Während des Projektseminars werden verschiedene Informationssysteme effektiv zur Unterstützung von Geschäftsprozessen zur Anwendung gebracht. Es werden Erfahrungen gesammelt, wie Ergebnisse einer Arbeit als Präsentation vorgestellt werden können und ein effektives Teamwork erreicht werden kann.
Jedes Seminar fokussiert andere Problemstellung, wie zum Beispiel: Wird zu Beginn der Veranstaltung zur Verfügung gestellt. Understanding management information systems and their impact on enterprise strategy and performance. This course is based on a textbook. The general idea of the course is that information systems knowledge is essential for creating competitive firms, managing global corporations, adding business value and providing useful products and services to customers.
The book provides an introduction to management information systems that students will find vital to their professional success. The growth of the Internet, social networks, the globalization of trade and the rise of information economies have recast the role of information systems in business and management.
Technology is supplying the foundation for new business models, new business processes, and new ways of distributing knowledge. Students have to prepare a number of cases and present their findings to the class.
Therefore, they will also be able to improve their presentation skills in this course. Digital Markets, Digital Goods 3. Optimization models and methods are the core of every planning step in management. Most of the actual planning problems can be modeled as linear or mixed-integer linear programs. The aim of this course is to understand the concept of this operations research technique, to be able to model various planning problems, and to solve those models by using a state-of-the-art software tool IBM ILOG CPLEX.
The main topics of the course are: The relevant material will be announced at the beginning of the course. Successful exam of Management Science. Successful development of an optimization model, testing and summarizing it a seminar paper of pages and a min. Aim of the course is deepening the knowledge in management science in particular in mixed integer programming.
Students will get familiar with state-of-the-art software tools and learn how to tackle practical planning problems. Developing planning models Solving mixed integer problems using state-of-the-art software tools Perform experiments and analyze results. Lecture notes and additional material are provided online. Presentations of special topics and case-studies by students.
Should be attended simultaneously or after the module "Service Operations Management". This workshop provides students with an opportunity to design a new service.
Students select a service industry of interest to them, perform an analysis of the competitive landscape, articulate the need of a new service relative to what already exists, and propose a design for a new service offering. The following steps help students through the exercise: Written exam min. The goal of the course is to study algorithms and methods that solves different problems that concern how to conduct and coordinate the operations i.
Many planning problems in operations management are difficult to solve under strict time constraints. Metaheuristic methods are state-of-the-art optimization techniques, which allow a fast planning also under difficult real-world constraints and time restrictions.
Aim of the course is to learn and understand the basic concepts of metaheuristics and its implementation in a high-level programming language Python. A Byte of Python.
Gendreau, Michel, and Jean-Yves Potvin. Successful exam of Optimization with Metaheuristics. Successful development and implementation of a metaheuristic, testing and summarizing it a seminar paper of pages and a min.
Aim of the course is deepening the knowledge in population-based metaheuristic methods. Students will get familiar with basic concepts of population-based evolutionary optimization methods and learn how to apply such methods to practical planning problems.
Aim of the course is to introduce students to problems arising in the management of production processes and make them familiar with traditional and recent approaches to address and solve these problems. The material of the course is mainly based on: Produktionsmanagement by Günther and Tempelmeier, Springer, Produktionsplannung by Domschke, Scholl and Voss, Springer, Learn programming using Visual Basic in a systematic way.
This course is an introduction to computer programming. Programming concepts as well as a modern programming language, Visual Basic, are taught. Visual Basic is easy to learn but still very powerful.
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