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Presentation
Presentation
This course offers a practical introduction to data analysis such that, as future researchers, the students can independently develop their own sample to population statistical analysis and/or interpret indicators generated from a statistical software package. Not only they will be able to decide upon a single random variable characteristics as to investigate relationships between variables (quantitative or categorical), with the goal of creating a model to predict a future value for some dependent variable or just to understand the type of relationship (if any) between variables. Contingency analysis and data tables
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT248-7322
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
1. Knowledge and Understanding analyse data (in an inference context) and interpret software outputs in order to produce information to help a decision maker. 2. Subject-Specific Skills Be familiar with the following topics: - Samples vs Population - Parameters, Estimates, Confidence Intervals and Hypothesis Testing - Central Limit Theorem - Independence, Correlation, Causation - Contingency Analysis - ANOVA - Linear Regression Analysis - Ordinary Least Squares
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Objectives
Objectives
Main topics will include (the assumption is that these topics should be already familiar to the students, analysed before e.g. during their undergraduate level studies): inference statistics and distributions, contingency analysis, analysis of variance, simple and multiple linear regression. Excel and Gretl (freeware) will be used to conduct the statistical analysis. Research papers will also be used as sources of indicators to be interpreted.
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Teaching methodologies and assessment
Teaching methodologies and assessment
Lectures in theorital-pratical regime with resources to softwares such as - Excl and Gretl (freeware). The evaluation consists: 1. Elaboration of one work - 50% of the final grade 2. Cases studies/Quizzes 2. Final test - 50% of the final grade
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References
References
Newbold, P., Carlson, W. &Thorne, B. (2013), Statistics for Business and Economics, 8th Ed. Prentice Hall Newbold, P., Carlson, W. &Thorne, B. (2007), Statistics for Business and Economics, 6th Ed. Prentice Hall (com exercícios online) Online resources: http://wps.prenhall.com/bp_newbold_statbuse_6/53/13699/3507189.cw/index.html Johnston, J. e Dinardo, John (2000), Métodos Econométricos, McGraw-Hill, 4th Ed
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Office Hours
Office Hours
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Mobility
Mobility
No