Applied Quantitative Methods for Management and Economics

Code:

2EAE04-2

Acronym:

MQAGE

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2015/2016 - 1S

Active?	Yes
Course/CS Responsible:	Master in Economics and Business Administration

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
EAE	61	Syllabus - 2015	1	-	7,5	56	202,5

Teaching language

Suitable for English-speaking students

Objectives

This course main goal is to show how quantitative methods can be applied to the analysis of management and economic problems to help in the decision making process that leads to the best solution available.

In a more practical and close to date framework, this course can also assist students to better appreciate published scientific research, and conveys the basic training for helping them to prepare the empirical part of their dissertations.

 

 

Learning outcomes and competences

By the end of this course, students are expected to be able to:

1.  Be acquainted with quantitative methods and statistical techniques in order to being able to apply them to specific economic and managerial problems.

2. Produce, estimate and interpret statistically and theoretically valid econometric models applied to management and economic contexts;

3. Comprehend, and critically assess research articles in scientific journals in managment and economics;

4. use appropriately software made available during the cour

 

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Students attending this course are expected to have a basic knowledge of Mathematics, Statistics and Economic Theory at the first year level of under-graduations in Economics and/or Business Management.

Program

Module 1:
1. Nonparametric tests
2. Analysis of variance
3. Univariate Linear time series models and forecasting

Module 2:

1. Classical Linear Regression Model (CLRM).
2. Dummy Variables.
3. Relaxing the CLRM hypotheses.
4. Non-stationary Time Series Models

Mandatory literature

Bento J. F. Murteira, Carlos S. Ribeiro, João A. e Silva, Carlos Pimenta; Introdução à Estatística, Escolar Editora, 2010
Webster, Allen; Estatística aplicada à administração e economia, McGraw Hill,, 2007
Murteira, Bento José Ferreira; Análise de sucessões cronológicas. ISBN: 972-9241-32-5
Oliveira, Manuel José Mendes de; Econometria. ISBN: 978-972-592-326-9
Gujarati, Damodar N; Basic econometrics. ISBN: 9780071276252

Complementary Bibliography

Wooldridge, Jeffrey M.; Introductory econometrics. ISBN: 0-324-11364-1
Dougherty, Christopher ; Introduction to Econometrics, Oxford University Press, 2007

Teaching methods and learning activities

Theoretical presentation of issues under concern, followed by practical examples for the students to solve with the appropriate software and, preferably, with actual data on the subjects addressed.

Software

Software R
EViews

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	100,00
Total:	100,00

Eligibility for exams

Época normal:
Distributed evaluation without final exam

1. There is no final exam, but only distributed evaluation without final exam.

2. There are two moments of individual assessment consisting in the realization of two tests: one corresponding to the module 1, being held after the presentation of all subjects pertaining to this module, and another corresponding to the module 2, being held after the end of the classes.

3. The final grade is the weighted average of the two tests (40% test of module 1 + 60% test of module 2).

4. If a student does not attend a test or does not hand in an assignment, a score of 0 will be given to that test or assignment.
 
5. Students fail this course if they attain a score lower than 6 on any assignment or test, regardless of the overall weighted score.

Época de recurso:

Final exam.

Calculation formula of final grade

CALCULATION IN DISTRIBUTED EVALUATION:

Mark of the module 1 test (Mod1)
Mark of the module 2 test  (Mod2)

Final Grade = 0.4*Mod1 + 0.6*Mod2

To pass this course, a student must obtain a minimum score of 6 marks (before rounding) in each of the tests. Additionally, to pass the course, a studant is required to obtain a final grade of, at least, 9.5.

Special assessment (TE, DA, ...)

In accordance with FEP.UP's evaluation regulations.

Classification improvement

In accorance with FEP.UP's evaluation regulations.