quantitative methods (2)
- 1. 190 COURSE DESCRIPTIONS: QUANTITAVE METHODS 14.9 QUANTITATIVE METHODS 30A00210 Mathematics and Statistics for Managers (6 cr) Responsible teacher: N.N. Status of the Course: Compulsory course Level of the Course: Fundamentals of Business Knowledge Teaching period: I-II Learning Outcomes: Learn to understand and use basic mathematical and statistical tools in solving and model- ing problems in economics and business. Provide skills for reading literature in economics and management science. Content: Mathematics: basic concepts of functions, vectors, matrices, systems of linear equations, linear pro- gramming. Statistics: population and sample, graphical data analysis, descriptive statistics, in- troduction to regression analysis, random num- bers. Assessment Methods and Criteria: 1. Lectures in mathematics 21 h and lectures in statistics 21 h. 2. Exercises 12 h in mathematics and 12 h in statistics. 3. The course can be completed by doing the exercises (20% of the final grade) and passing two midterm exams (80% of the final grade), or by passing the final exam. Literature: Knut Sydsæter and Peter Hammond (2008) Es- sential mathematics for economic analysis 3rd edition. ; Pace, L. (2010) Statistical Analysis Using Excel 2007. Study Material: Complementary/alternative readings: Simon, C.P. & Blume, L.: Mathematics for Economists Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30A00210/ Prerequisites High school mathematics Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English Further Information: Only one of the courses 30A00110 Matematiikkaa ja tilastotiedettä liikkeenjohtajille and 30A00210 Mathematics and statistics for managers can be included in the Bachelor‟s degree. 30A00410 Quantitative Business Analysis (6 cr) Responsible teacher: Dr. Pekka Malo and N.N. Status of the Course: Compulsory course Level of the Course: Fundamentals of Business Knowledge Learning Outcomes: To improve mathematical and statistical skills for problem solving, and to create theoretical founda- tions for further studies and understanding eco- nomic reference texts. This course is a continuum for Mathematics and Statistics for Managers (30A00210). Content: Mathematics: derivative and partial derivative, integral calculus, foundations of unconstrained optimization and constrained optimization. Statis- tics: inference based on probability, conditional probability and Bayes formula. Random variable and its distribution, expectation, variance and standard deviation, decision trees, descriptive statistics, confidence intervals and hypothesis testing. Assessment Methods and Criteria: 1. Lectures in mathematics 21 h, Dr. Pekka Malo. and lectures in statistics 21 h, N.N. 2. Exercises in mathematics 12 h, N.N.. and exercises in statistics 12 h, N.N. 3. The course can be completed by doing the exercises (20% of the final grade) and passing two midterm exams (80% of the final grade) or by passing the final exam. Literature:
- 2. COURSE DESCRIPTIONS: QUANTITAVE METHODS 191 Knut Sydsæter and Peter Hammond (2008) Es- sential mathematics for economic analysis 3rd edition. ; Pace, L. (2010) Statistical Analysis Using Excel 2007. Study Material: Complementary/alternative readings: Simon, C.P. & Blume, L.: Mathematics for Economists, W.W. Norton & Co, 1994. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30A00410/ Prerequisites: 30A00210 Mathematics and statistics for manag- ers Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English Further Information: Only one of the courses 30A00310 Kvantitatii- vinen analyysi taloustieteissä and 30A00410 Quantitative business analysis can be included in the Bachelor‟s degree. 30C00100 Statistical Analysis (6 cr) Responsible teacher: Jan-Otto Malmberg Status of the Course: BT BSc program, common program studies B.Sc., finance (Taloushallinto) Level of the Course: Intermediate Teaching period: III - IV Workload: - Lectures 40 h - Exercises 20 h - Independent work 102 h Total 162 h Learning Outcomes: The course will provide students with additional knowledge in statistical theory and techniques. Content: Probability, conditional probability, decision trees, probability distributions, estimation, hy- pothesis testing. Introduction to regression analy- sis, analysis of variance. Assessment Methods and Criteria: 1. Lectures 40 h, Jan-Otto Malmberg. 2. Exercises 20 h, N.N. 3. The course can be completed by doing the exercises (20% of the final grade) and passing two midterm exams (80% of the final grade) or by passing the final exam. Literature: Levine, David M. (2006) Business statistics a first course. ISBN 0131971018 Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30C00100/ Prerequisites: Compulsory courses in quantitative methods Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English 30C00200 Econometrics (6 cr) Responsible teacher: Professor Timo Kuosmanen Status of the Course: B.Sc., business technology, specialization studies B.Sc., economics program B.Sc., finance (Taloushallinto) Level of the Course: Intermediate Teaching period: III Workload: - Lectures 40 h - Exercises 20 h - Independent work 102 h - Total 162 h Learning Outcomes:
- 3. 192 COURSE DESCRIPTIONS: QUANTITAVE METHODS The main objective of the course is to obtain a basic understanding of the econometric method. The course focuses on least squares estimation and related statistical inferences. The assumptions of least squares estimation will be critically inves- tigated, and possible ways to alleviate the assump- tions will be explored. Content: Linear regression model and its assumptions, least squares estimation, tests of parameters and linear restrictions, endogeneity and instrumental variables, heteroskedasticity and autocorrelation. Introduction to maximum likelihood estimation of discrete choice models and limited dependent variables. Introduction to time series and panel data models. All topics are examined by means of economic examples with real empirical data. Assessment Methods and Criteria: 1. Lectures 40 h, Timo Kuosmanen 2. Exercises and demonstrations 20 h, Antti Saastamoinen 3. Grading is based on exercises (30%) and the final exam (70%). Literature: Dougherty, Christopher (2007) Introduction to econometrics. ISBN 9780199280964 Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30C00200/ Prerequisites: Compulsory courses in quantitative methods Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English 30C00300 Mathematical Methods for Economists (6 cr) Responsible teacher: N.N Status of the Course: BSc, BT program, specialization studies BSc, economics program Level of the Course: Intermediate Teaching period: III - IV Workload: Contact hours 62 h and autonomous work 100 h Learning Outcomes: To improve mathematical skills acquired in the basic courses Content: The course concentrates on mathematical meth- ods useful in economics and business. The topics covered are essentials of set theory, matrix alge- bra, multivariate calculus, optimization, introduc- tion to dynamics: difference and differential equa- tions. The applications of the course will cover different areas in economics and management, finance, business technology and logistics. Com- puters are used to solve some of the problems. Assessment Methods and Criteria: 1. 40 h lectures + 22 h exercises + 20 h optional instruction sessions. 2. The course can be completed by doing exer- cises (20% of the final grade) and by pssing two midterm exams (80% of the final grade) or by passing the final exam. Literature: Simon, Carl P. and Blume, Lawrence (1994) Mathematics for Economists. ISBN 0393957330 ; Sydsaeter K., Hammond P., Seierstad A., Strom A. (2008) Further mathematics for economic analy- sis, 2nd edition. ; Sydsäter, K. & Hammond, P (2008) Essential Mathematics for Economic Analysis, 3rd edition. Study Material: Lecture notes Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30C00300/ Prerequisites: Compulsory courses in quantitative methods Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English 30C00400 Tools for Business Decisions 2 (6 cr)
- 4. COURSE DESCRIPTIONS: QUANTITAVE METHODS 193 Responsible teacher: N.N Status of the Course: Bachelor‟s program in Business Technology, common program studies Level of the Course: Intermediate studies Teaching period: IV Workload: - Lectures 42 h - Independent work 120 h Learning Outcomes: To familiarize the students with useful analytical tools applied to practical business decisions. Content: Decision making under uncertainty, utility theory, multiple criteria decision making, waiting line models, simulation, with cases. Modeling with spreadsheets and add-inns. Assessment Methods and Criteria: 1. Lectures and demonstrations 42h 2. Exercises/cases and final exam Literature: Anderson, D.R., Sweeney, D.J., and Williams, T.A. (2010) An Introduction to Management Science. ISBN 978-1439043271 Study Material: PP-slides, handouts, cases/exercises, textbook Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30C00400/ Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English 30E00150 Applied Optimization and Methodologies (6 cr) Responsible teacher: Kalyanmoy Deb Status of the Course: Elective course. This course is intended both for master's and doctoral students. Level of the Course: Advanced Teaching period: Summer 2012 Workload: - lectures 42 h - individual work 120 h Learning Outcomes: The objective of the course is to acquaint students with optimization methods for single and multiple objective problems. Both classical and evolution- ary algorithms for optimization are discussed. Content: Introduction to optimality conditions, classical optimization methods, constraint handling basics, introduction to evolutionary optimization (EO), cases studies from real-world problems, custom- ized EO, uncertainty based EO, robust and relia- bility based EO, multi-objective EO, innovation through optimization, and decision-making. Assessment Methods and Criteria: 1. Lectures and participation (10 %) 2. Exercises (20 %) 3. Project (20 %) 4. Exam (50 %) Literature: 1. Bazaraa, M. S., Sherali, H. D. and Shetty, C. M. (2004). Nonlinear programming: Theorey and algorithms. Wliey: London. 2. Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. Wiley: London. Study Material: Lecture slides, handouts, exercises, textbook. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30E00150/ Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English
- 5. 194 COURSE DESCRIPTIONS: QUANTITAVE METHODS 30E00400 Simulation (6 cr) Responsible teacher: prof. Tomi Seppälä Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, elective course of advanced spe- cialization studies. Level of the Course: Advanced Teaching period: I Workload: - Lectures 40 h - Exercises 20 h - Project 50 h - Independent work 52 h Learning Outcomes: To acquaint the student with modeling using sim- ulation techniques which can be usedto support management decision making, especially in fi- nance, operations management, and logistics; to develop expertise in using simulation models with computers and related software,especially Excel; to give you experience in analyzing results and making decisions through assigned homework exercises and case analyses. Content: Introduction to simulation models, simulation in Excel, random numbers, methods to simulate random events, managerial applications of risk analysis, Wiener process, valuation of stocks and options, system simulation, forecasting, advanced simulation techniques. Assessment Methods and Criteria: 1. Lectures 40 h 2. Exercises 20 h 3. The grade consists of final exam (50%), exer- cises (20%) and project work (30%). Literature: Evans, J.R. & Olson, D.L. (2002) Introduction to simulation and risk analysis. ; Vose, D. (2000) Risk analysis: a quantitative guide. ; Ross, Shel- don M. (2006) Simulation. ISBN 9780125980630 Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30E00400/ https://noppa.aalto.fi/noppa/kurssi/30C00400/ Prerequisites: Undergraduate mathematics, statistics and prob- ability, as well as Excel skills. More specifically, basic knowledge in matrix algebra, differential and integral calculus, statistical analysis and probability distributions are essential. Evaluation: 0-5 Registration for Courses: Via WebOodi Language of Instruction: English Further Information: Lectures and exercises in period I. Project work and project presentations in period II. 30E00500 Quantitative Empirical Research (6 cr) Responsible teacher: Prof. Pekka Korhonen and Dr. Pekka Malo Status of the Course: Common Scientific Doctoral Studies Master‟s degree, Minor studies in Quantitative Methods Level of the Course: Advanced Teaching period: IV Workload: - Lectures 40 h - Exercises 20 h - Independent work 102 h Learning Outcomes: The objective of the course is to enable the stu- dents to use quantitative data analysis techniques in business and economic research. The course will provide the students with a set of tools useful in empirical research. Content: Basic concepts, screening data, and visualizing multivariate observations are discussed. Further- more, the course will define and introduce a set of statistical multivariate methods and explain when their use is appropriate and how they are related to each other. Some of the methods covered are linear regression, logistic regression analysis,
- 6. COURSE DESCRIPTIONS: QUANTITAVE METHODS 195 principal component analysis, factor analysis, analysis of variance, and cluster analysis. Method- ological aspects and interpretation of analysis are also explained. Excel and SAS programs will be used in exercises and demonstrations during the course. Assessment Methods and Criteria: 1. Preliminary assignments 2. Lectures 42 h 3. Exercises 18 h 4. Grading is based on a final exam (80% of the grade) and exercises (20% of the grade) Literature: Sharma, Subhash (1996) Applied multivariate techniques. ISBN 0-471-31064-6 ; Hair J.H., Tat- ham R.L., Anderson R.E.A., Black W. (1998) Mul- tivariate data analysis. ISBN 0138948585 Study Material: Other material announced by the lecturers. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30E00500/ https://noppa.aalto.fi/noppa/kurssi/30C00500/ Prerequisites: Basic knowledge in mathematics and statistics is assumed. Moreover, basic knowledge in linear algebra and statistical analysis are recommended. Evaluation: 0-5 Registration for Courses: Via Weboodi Language of Instruction: English 30E00700 Advanced Statistical Methods (6 cr) Responsible teacher: Prof. Tomi Seppälä Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, elective course of advanced spe- cialization studies. M.Sc.(Econ), finance program, advanced speciali- zation studies. Level of the Course: Advanced Teaching period: III Workload: - Lectures 40 h - Exercises 20 h - Project 50 h - Independent work 52 h Learning Outcomes: To expand and deepen the student‟s knowledge of and ability to use regression and time series anal- ysis with applications to business, finance and economics. Content: Topics in linear models and Time Series analysis: special estimation methods of regression models, ARMA models, forecasting, cointegration, ARCH and GARCH models. The content may change from year to year. Assessment Methods and Criteria: 1. Lectures 40 h, professor Tomi Seppälä 2. Exercises 20 h, Tomi Seppälä 3. The grade consists of a final exam (50%), ex- ercises (20%) and a project (30%). Literature: Brooks, Chris (2008) Introductory econometrics for finance, 2nd edition. ISBN 0-521-79018-2 ; Verbeek, Marno (2004) Guide to modern econo- metrics. ISBN 978-0-470-85773-1 ; Enders, Wal- ter (2003) Applied Econometric Time Series, 2nd Edition. ISBN 978-0471230656 Course Homepage: https://noppa.aalto.fi/noppa/kurssi/30E00700/ https://noppa.aalto.fi/noppa/kurssi/30C00700/ Prerequisites: Compulsory statistics and mathematics courses in the Bachelor‟s program, as well as at least one of the following: introduction to econometrics, sta- tistical analysis or simulation. It is important that student knows the basics of statistical testing and regression analysis prior to attending the course. Other prior courses in quantitative areas are use- ful, too. Evaluation: 0-5 Registration for Courses: Via Weboodi Language of Instruction: English
- 7. 196 COURSE DESCRIPTIONS: QUANTITAVE METHODS Further Information: Lectures and exercises in period III. Project work and project presentation in period IV 57C99901 Bachelor’s Thesis (10 cr) Responsible teacher: Assistant Professor, Ph.D. (econ.) Johanna Bragge (with Merja Halme and Markku Kuula) Status of the Course: B.Sc. (Econ.), Business Technology program. Level of the Course: Compulsory program course. Teaching period: I-II (Autumn) and III-IV (Spring) Workload: - Independent scientific work: 267 h - searching and reading literature - formulating a research question - (doing empirical analyses, gathering research data) - writing the thesis Learning Outcomes: The objective is to learn and practice independent scientific thinking by setting up research ques- tions and studying a specific topic. Students learn to get to know references, to find literature, and to apply it for resolving a research question. The thesis will be a structured, scientific report. Content: The Bachelor‟s Thesis is carried out together with Bachelor‟s Thesis Seminar (57C99902) Assessment Methods and Criteria: Grading: 85% of the grade is based on the thesis and 15% is based on participation in the thesis seminar. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57C99901/ Evaluation: 0-5 Registration for Courses: Register to 57C99902 Bachelor‟s Thesis Seminar via Weboodi. Language of Instruction: English 57C99902 Bachelor’s Thesis Seminar (2 cr) Responsible teacher: Assistant Professor, Ph.D. (econ.) Johanna Bragge (with Merja Halme and Markku Kuula) Status of the Course: B.Sc. (Econ.), Business Technology program. Level of the Course: Compulsory program course Teaching period: I-II (Autumn) and III-IV (Spring) Workload: - introductory lectures 8 h - seminar sessions 14 h - preparing for lectures 6 h - preparing for seminar sessions 12 h - doing assignments (research plan, research profiling assignment) 13 h Learning Outcomes: The objective is to learn and practice independent scientific work. Content: In the seminar, students get guidance in their research for Bachelor‟s Thesis. During the Thesis seminar, students will prepare a research plan, conduct a research profiling assignment, report the progress of their Thesis, present and defend their research results, act twice as an opponent, and participate actively in seminar discussions. Assessment Methods and Criteria: 3. Introductory lectures and seminar sessions 28 h 4. Requirements for passing the seminar: com- pleting the research profiling assignment, pre- senting own thesis at the seminar, acting twice as an opponent, attending to 70% of the semi- nar sessions (Grading: Pass/Fail) Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57C99902/ Evaluation: Pass/Fail Registration for Courses: via WebOodi. Language of Instruction:
- 8. COURSE DESCRIPTIONS: QUANTITAVE METHODS 197 English 57C99903 Maturity Test (0 op) Responsible teacher: Thesis supervisor Status of the Course: B.Sc. (Econ.), Business Technology program. Level of the Course: Compulsory program course. Teaching period: I-II (Autumn) and III-IV (Spring) Learning Outcomes: After finalizing the Bachelor‟s Thesis, students carry out a proficiency test in mother tongue. The objective is to show that a student can write an essay in her or his mother tongue and that s/he masters the basic concepts in her or his thesis. In general, the test is written in Finnish, but non- Finnish speakers are granted an exemption to write the test in English. Content: The Maturity Test is taken at the end of the Bache- lor‟s Thesis Seminar (57C99902) and Bachelor‟s Thesis (57C99901). The test can be taken in con- nection with any official exam, and the date is agreed upon with the supervisor once the thesis is written. Assessment, Methods and Criteria: Exam 4 h Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57C99902 Evaluation: Pass/Fail Registration for Courses: Register first to 57C99902 Bachelor‟s Thesis Sem- inar via WebOodi. Agree the date for the Profi- ciency Test with the supervising teacher (after the thesis is written). 57E00500 Business Intelligence (6 cr) Responsible teacher: Oana Velcu Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, common advanced course Level of the Course: Specialization course Teaching period: 12th March 2012 - 11th May (IV Spring) Workload: - Lectures 28 hours - Preparing for lectures 56 hours - Case studies 4.5 hours - Preparing for case studies 14 hours - Preparing for exercises 10 hours - Computer labs 4.5 hours - Preparing for computer labs 9 hours - Preparing for exam 30 hours - Exam 4 hours Learning Outcomes: After the course, the students will understand the connection between the analytical tools that can be used on real data in companies and the strate- gic decision-making. The students will have ana- lytical skills that enable them to work with the data, to understand it and turn it into intelligence for particular decisional contexts. Content: The course seeks to provide a balanced approach to BI by enabling insight into the building blocks of BI, such as data management, querying, analyt- ic tools, quantitative modeling, and reporting, with the purpose to enable students acquire theo- retical and practical understanding of decision- making and problem solving. Assessment Methods and Criteria: 4. Exam 60% 5. Case study essays 20% 6. Exercises 20% Literature: Turban, Efraim, Sharda R., and Delen, D. (2011) Decision support and business intelligence sys- tems 9th ed.. ISBN 0132453231 Study Material: Other research papers and material provided by lecturers. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57E00500/ Evaluation: 0-5 Registration for Courses:
- 9. 198 COURSE DESCRIPTIONS: QUANTITAVE METHODS Via WebOodi Language of Instruction: English 57E99901 Master’s Thesis (30 cr) Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, compulsory course. Level of the Course: Advanced Learning Outcomes: The objective is to practice independent scientific thinking by setting up research questions and studying a specific research topic. The thesis will be a structured, scientific report. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57E99901/ Evaluation: 0-5 Further Information: The Master‟s Thesis needs to be carried out to- gether with the Master‟s Thesis Seminar (57E99902). 57E99902 Master’s Thesis Seminar (0 cr) Responsible teacher: Matti Rossi (coordinates) Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, compulsory course. Level of the Course: Advanced Teaching period: I - IV Workload: - 6 h presentations - 4 h critique - 20 h seminars Learning Outcomes: The objective is to practice independent scientific thinking by setting up research questions and studying a specific research topic. The thesis will be a structured, scientific report. Content: In the seminar, students get guidance in their research for Master‟s Thesis. There are lecturers on methods and theories of study in IS, MS and OR. Assessment Me Course Homepage: https://noppa.aalto.fi/noppa/kurssi/38E00100/ thods and Criteria: Lectures, presentations and critique of other stu- dents work. If necessary, students will be orga- nized into smaller groups supervised by professors from the department of Information and Service Economy. Course Homepage: https://noppa.aalto.fi/noppa/kurssi/57E99902 Evaluation: hyväksytty/hylätty Registration for Courses: Via WebOodi Language of Instruction: English 57E99903 Maturity Test (0 op) Status of the Course: M.Sc.(Econ), Information and Service Manage- ment program, compulsory course. Level of the Course: Advanced Learning Outcomes: After finalizing the Master‟s Thesis, students carry out a proficiency test in Mother Tongue. The ob- jective is to show a student can write an essay in her or his mother tongue and that she or he knows the basic concepts in her or his Thesis. Evaluation: hyväksytty/hylätty