First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Economics and Political Science
ENTREPRENEURSHIP AND INNOVATION
Course unit
STATISTICS FOR MANAGEMENT
EPP6077104, A.A. 2017/18

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

Information on the course unit
Degree course Second cycle degree in
ENTREPRENEURSHIP AND INNOVATION
EP2372, Degree course structure A.Y. 2017/18, A.Y. 2017/18
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Number of ECTS credits allocated 8.0
Type of assessment Mark
Course unit English denomination STATISTICS FOR MANAGEMENT
Department of reference Department of Economics and Management
Mandatory attendance No
Language of instruction English
Branch PADOVA
Single Course unit The Course unit CANNOT 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 ANNA GIRALDO SECS-S/03
Other lecturers MAURO BERNARDI SECS-S/03

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
EPP7082021 STATISTICS FOR MANAGEMENT ANNA GIRALDO EP2423

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-S/03 Statistics for Economics 8.0

Mode of delivery (when and how)
Period Second semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Lecture 8.0 56 144.0 No turn

Calendar
Start of activities 26/02/2018
End of activities 01/06/2018

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: Statistical analysis of data in the economics and the management fields.
Examination methods: Written exam.
Assessment criteria: Knowledge of some techniques to analyse economic data and ability to apply them to real cases.
Course unit contents: Brief review of inferential statistics
The linear regression model: definition, inference, goodness of fit
Regression for binary dependent variables
Forecasting
Introduction to time series analysis
Forecasting with time series: Moving Averages and Smoothing Methods
Introduction to market segmentation (cluster analysis)

Analysis of real cases with the statistical software R
Planned learning activities and teaching methods: Lectures and practical lectures in the computer lab.
Additional notes about suggested reading: Study materials will be uploaded on the moodle.
Textbooks (and optional supplementary readings)
  • Hanke, John E.; Wichern, Dean, Business Forecasting. Harlow: Pearson, 2014. Cerca nel catalogo