First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
DATA SCIENCE
Course unit
BUSINESS ECONOMIC AND FINANCIAL DATA
SCP7079231, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
DATA SCIENCE
SC2377, Degree course structure A.Y. 2017/18, A.Y. 2018/19
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination BUSINESS ECONOMIC AND FINANCIAL DATA
Website of the academic structure http://datascience.scienze.unipd.it/2018/laurea_magistrale
Department of reference Department of Mathematics
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge MAURO BERNARDI SECS-S/03
Other lecturers OMAR PACCAGNELLA SECS-S/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-S/03 Statistics for Economics 6.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 01/10/2018
End of activities 18/01/2019

Examination board
Examination board not defined

Syllabus
Prerequisites: Basic statistics: descriptive statistics and probability. Inferential statistics: estimation, confidence intervals and hypothesis testing.
Target skills and knowledge: This course aims at introducing the students to the main statistical features and concepts underlying the analysis of data collected over time, as well as providing the basic statistical solutions to analyse such data in economic, financial and business settings.
Examination methods: Homework and Final Presentation.
Assessment criteria: Students will be evaluated according to their level of knowledge of some tools and techniques to analyse economic, financial or business data and their ability to apply them to real cases.
Course unit contents: Decomposing and analysing economic time series: latent component approaches and ARMA modelling.
Enhancing the analysis of economic and financial time series data: some case studies.
Business and marketing data analyses: the joint use of cross-sectional and temporal dimension and the introduction of dynamic modelling.
Planned learning activities and teaching methods: Lectures and Laboratories. Working in groups.
Additional notes about suggested reading: Notes prepared by the teaching staff will be uploaded throughout the course.
Textbooks (and optional supplementary readings)
  • Fitzmaurice G.M., Laird N.M. and J.H. Ware, Applied Longitudinal Analysis. --: Wiley, 2011. 2nd ed. Cerca nel catalogo
  • Leeflang P.S.H., Wittink D.R., Wedel M. and P.A. Naert, Building Models for Marketing Decisions. --: Springer, 2000. Cerca nel catalogo
  • Martin V., Hurn S. and D. Harris, Econometric Modelling with Time Series: Specification, Estimation and Testing. --: Cambridge University Press, 2012. Cerca nel catalogo
  • Wooldridge J.M., Econometric Analysis of Cross Section and Panel Data. --: The MIT Press, 2010. 2nd ed. Cerca nel catalogo