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Course Description
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Course Name
Research Techniques
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Host University
Universidad Carlos III de Madrid
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Location
Madrid, Spain
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Area of Study
Business Administration, Economics, Entrepreneurship, Finance, Management, Marketing, Mathematics, Research, Statistics
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Language Level
Taught In English
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Prerequisites
STUDENTS ARE EXPECTED TO HAVE COMPLETED
This course assumes that the student knows the contents of
a) Statistics I (http://www3.uc3m.es/reina/Fichas/Idioma_2/204.13154.html),
b) Statistics II (http://www3.uc3m.es/reina/Fichas/Idioma_2/204.13160.html),
and the lesson of Properties of Matrices in
c) Mathematics for Economics II (http://www3.uc3m.es/reina/Fichas/Idioma_2/204.13156.html)
in the Business Administration degree.
In case of not having taken these courses or the equivalent ones, the student is the responsible of being updated of these contents in order to be able to follow the lessons. -
Course Level Recommendations
Upper
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
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ECTS Credits
6 -
Recommended U.S. Semester Credits3
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Recommended U.S. Quarter Units4
Hours & Credits
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Overview
COMPETENCES AND SKILLS THAT WILL BE ACQUIRED AND LEARNING RESULTS. SPECIFIC COMPETENCES:
1. Learning the basic Mathematical and Statistical skills for the analysis of multivariate socioeconomical
data such as those coming from a market research.2. Learning advance Statistical techniques for the description of quantitative multivariate socioeconomical data: Principal Components Analysis.
3. Learning advance Statistical techniques to analyze socio-economical data in the form of a
matrix of distances or disparities: Multidimensional Scaling.4. Learning advance Statistical techniques for the description of quantitative multivariate socioeconomical data: Simple and Multiple Correspondence Analysis.
5. Being able to describe and analyze real data sets using the techniques mentioned above.
6. Being able to elaborate reports with the results of the analysis of real case studies.
CROSS COMPETENCES
1. Solving real case studies.
2. Learning and training in the use of Statistical software to solve real case studies.
3. Critical and selective reasoning to solve real life problems.
4. Presentation abilities.DESCRIPTION OF CONTENTS: PROGRAMME
1. Introduction: Matrix algebra, basic statistical descriptives and distances.
2. Principal Components Analysis.
3. Multidimensional Scaling.
4. Simple and Multiple Correspondence Analysis.
5. Cluster Analysis.
6. Discriminant Analysis.LEARNING ACTIVITIES AND METHODOLOGY
1. Theoretical lectures (4 ECTS)
2. Computer labs (2 ECTS)
3. Final project.ASSESSMENT SYSTEM
60%: Continuous evaluation and/or final exam.
40%: Handing and presenting a final project.
% end-of-term-examination: 60
% of continuous assessment (assigments, laboratory, practicals?): 40BASIC BIBLIOGRAPHY
- Johnson, Richard A. y Wichern, Dean W. Applied Multivariate Statistical Analysis, Prentice Hall, 1982
- Rencher, Alvin C Multivariate Statistical Inference and Applications, Wiley, 1998
- Härdle, Wolfgang K. and Simar, Léopold Applied Multivariate Statistical Analysis, Springer, 2012 (3rd ed.)ADITIONAL BIBLIOGRAPHY
- Greenacre, Michael J. Theory and Applications of Correspondence Analysis, Academic Press, Inc., 1984
Course Disclaimer
Please note that there are no beginning level Spanish courses offered in this program.
Courses and course hours of instruction are subject to change.
Eligibility for courses may be subject to a placement exam and/or pre-requisites.
Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.
ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.
Please reference fall and spring course lists as not all courses are taught during both semesters.
Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations
Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.