First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
STATISTICS FOR ECONOMICS AND BUSINESS
Course unit
BUSINESS STATISTICS
SCP4063713, A.A. 2019/20

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

Information on the course unit
Degree course First cycle degree in
STATISTICS FOR ECONOMICS AND BUSINESS
SC2095, Degree course structure A.Y. 2014/15, A.Y. 2019/20
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination BUSINESS STATISTICS
Website of the academic structure http://www.stat.unipd.it/studiare/ammissione-lauree-triennali
Department of reference Department of Statistical Sciences
E-Learning website https://elearning.unipd.it/stat/course/view.php?idnumber=2019-SC2095-000ZZ-2017-SCP4063713-N0
Mandatory attendance No
Language of instruction Italian
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 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 9.0

Course unit organization
Period Second semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Laboratory 2.0 16 34.0 No turn
Lecture 7.0 48 127.0 No turn

Calendar
Start of activities 02/03/2020
End of activities 12/06/2020
Show course schedule 2019/20 Reg.2014 course timetable

Examination board
Examination board not defined

Syllabus
Prerequisites: Statistical Models 1
Target skills and knowledge: The course aims at providing a set of tools and statistical models, useful for data analysis and forecasting in business and marketing.
the course main features are the analysis of case studies based on real data, forecast evaluation and interpretation of results in a business perspective, by applying the proposed methods.
Examination methods: The final exam is composed of two parts:

1. Written test with questions and exercises concerning the course program
2. Working group on a business case, selected by students and arranged with instructor, with final oral presentation.
Assessment criteria: The examination will positively evaluate:
-preparation on the specific topics of the course
-ability to interpret results from a statistical and business perspective
-ability to formulate a business recommendation
Course unit contents: - Business forecasting: methods and models
- Performance evaluation: prediction accuracy measures
- Smoothing methods
- Box-Jenkins methodology for ARIMA models
- Linear regression with time series data: multicollinearity, trend, seasonality, residual autocorrelation
- Nonlinear regression: product life cycle models
- Case studies
Planned learning activities and teaching methods: The course is organized on 48 hs of lecture and 16 hs of computer activity.
During the course, students are required to realize a working group on a business forecasting problem.
The working group gives the possibility to develop soft skills, such as: problem solving, ability to work in group, reporting and presentation of results.
Additional notes about suggested reading: Reference books are indicated by the instructor.
Slides and data set are also provided during the course.
Textbooks (and optional supplementary readings)
  • Hyndman, Rob J., Athanasopoulos, George, Forecasting: Principles and Practice. --: OTexts, 2014. Cerca nel catalogo
  • Muller, Eitan; Peres, Renana; Mahajan, V., Innovation Diffusion and New Product Growth. Cambridge: Marketing Science Institute, 2011. Cerca nel catalogo
  • Hanke, John E.; Wichern, Dean W., Business forecastingJohn E. Hanke, Dean W Wichern. Upper Saddle River: Pearson, 2009.

Innovative teaching methods: Teaching and learning strategies
  • Case study
  • Working in group
  • Story telling
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Latex

Sustainable Development Goals (SDGs)
Quality Education Industry, Innovation and Infrastructure