ISCTE-IUL > Education > MGE

Data Analysis, Modelling and Research (1 º Sem 2017/2018)

Code:	M1503
Acronym:	M1503
Level:	2nd Cycle
Basic:	Yes
Teaching Language(s):	English, Portuguese
Friendly languages:

Be English-friendly or any other language-friendly means that UC is taught in a language but can either of the following conditions:
1. There are support materials in English / other language;
2. There are exercises, tests and exams in English / other language;
3. There is a possibility to present written or oral work in English / other language.

Semester	ECTS Credits	Theoretical Lesson (T)	Theoretical and Pratical Lesson (TP)	Practical and laboratorial lesson (PL)	Seminary (S)	Field Work (TC)	Training Period (E)	Tutorial Orientation (OT)	Contact Hours	Autonomous Work	Others (O)	Total Load Hours [?]Contact Hours + Autonomous Work
1	6.0	0.0 h/sem	30.0 h/sem	0.0 h/sem	0.0 h/sem	0.0 h/sem	0.0 h/sem	1.0 h/sem	31.0 h/sem	119.0 h/sem	0.0 h/sem	150.0 h/sem


Since year	2016/2017
Pre-requisites	NA
Objectives	The main purpose of this course is to enable students to apply univariate and multivariate data analyses to real situations in business and institutional environments.
Program	1) Preliminary exploratory data analysis. 2) Parametric hypothesis tests: one-sample t-test; independent samples t-test; one-way ANOVA. 3) Non-parametric hypothesis tests: Kolmogorov-Smirnov test for normality; Chi-square test for independence; Mann-Whitney test; Kruskal-Wallis test. 4) Linear Regression: Simple and Multiple 5) Models with binary dependent variable: LOGIT and PROBIT Principal Components Analysis.
Evaluation Method	The evaluation takes place in two periods: Regular (or first season) and Re-sitting (or second season). In the Regular Season students must have a minimum of 80% attendance and will be evaluated as follows: a) Team work (40%). b) One final exam (60%) covering the entire subjects - the score must be at least 8.5 points. Score must be at least 10 points in order to get approval on this course. In the written assessment students can use a form, statistical tables, and a calculator.
Teaching Method	The teaching-learning methodology (LM) includes three different components: 1. Expositional, for the presentation of the theoretical reference frames 2. Experimental laboratory, with the development and operationalization of computer models 3. Self-study, related with autonomous work by the student
Observations
Basic Bibliographic	1) Hair Jr et al., Multivariate data analysis: a global perspective, 7th ed, 2010. 2) McClave, James T., Benson, P. G. and Sincich, T. (2012), {\it Statistics for Business and Economics}, 12th edition. 3) Wooldridge, Jeffrey M. (2015), Introductory Econometrics: A Modern Approach, South-Western, 5th Edition 4) José Dias Curto, José C. Pinto, Ana Morais and Isabel Lourenço (2011), "The heteroskedasticity-consistent covariance estimator in accounting", Rev of Quant Finance and Accounting, 37 (4), 427-449. 5) José Dias Curto and José C. Pinto (2011), "The Corrected VIF (CVIF)", Journal of Applied Statistics, 38 (7), 1499-1507. 6) José Dias Curto and José C. Pinto (2009), "The coefficient of variation asymptotic distribution in case of Non-iid random variables", Journal of Applied Statistics, Vol. 36, No. 1, 21-32. 7) José Dias Curto and José C. Pinto (2007), "New Multicollinearity indicators in linear regression models", Int. Statistical Review, 75 (1), 114-121.
Complementar Bibliographic	1) Curto, J. Dias (2016), Estatística: muitas aplicações em Excel e poucas fórmulas..., Ed. Autor. https://fenix.iscte-iul.pt/homepage/jjdc@iscte.pt/livro_estatistica 2) Elizabeth Reis, Paulo Melo, Rosa Andrade e Teresa Calapez, Estatística Aplicada, vol. 2, 5ª ed., Edições Sílabo, 2003. 3) Erik Mooi e Marko Sarstedt, A Concise Guide to Market Research: the Process, Data, and Methods using IBS SPSS Statistics, Springer, 2011. 4) João Maroco, Análise Estatística com PASW Statistics (ex-SPSS), Edições ReportNumber, 2010. 5) Maria de Fátima Salgueiro, Paula Vicente, Elizabeth Reis e Dias Curto - Apontamentos de apoio à UC de Análise de Dados / Coursenotes, Mestrado de Gestão, 2014/2015. 6) Paul Newbold, William Carlson and Betty Thorne, Statistics for Business and Economics, 7th ed., 2009. 7) Raúl Laureano e Maria do Carmo Botelho, SPSS: O meu Manual de Consulta Rápida, Edições Sílabo, 2010. 8) Raúl Laureano, Testes de Hipóteses com o SPSS: O meu Manual de Consulta Rápida, Edições Sílabo, 2011. 9) Isabel Costa Lourenço, Manuel Castelo Branco and José Dias Curto (2012), "The value relevance of reputation for sustainability leadership", Journal of Business Ethics, forthcoming. 10) Isabel Costa Lourenço, Manuel Castelo Branco, José Dias Curto and Teresa Eugénio (2012), "How Does the Market Value Corporate Sustainability Performance?" Journal of Business Ethics, 108, 417-428. 11) Isabel Costa Lourenço, S. Fernandes and José Dias Curto (2012), "How Does the Market View Interests in Jointly Controlled Entities?", Spanish Journal of Finance and Accounting, Vol. XLI (153), 119-14. 12) José Dias Curto and José Castro Pinto (2012), "Predicting the Financial Crisis Volatility", Economic Computation And Economic Cybernetics Studies and Research Journal, 46 (1), 183-195. 13) Luís Oliveira, José Dias Curto and João Pedro Nunes (2011), "The Determinants of Sovereign Credit Spread Changes in the Euro Zone", Journal of International Financial Markets, Institutions & Money, 22, 278-304. 14) José Dias Curto, João Amaral Tomaz and José Castro Pinto (2009), "A new approach to bad news effects on volatility: the Multiple-Sign-Volume sensitive regime EGARCH model (MSV-EGARCH), Portuguese Economic Journal, 8, 23-36; 15) José Dias Curto, José Castro Pinto and Gonçalo Tavares (2009), "Modelling stock markets' volatility using GARCH models with Normal, Student's t and stable Paretian distributions, Statistical Papers, Volume 50 (2), 311-321.