STATISTICAL METHODS FOR MANAGEMENT
cod. 1005198

Academic year 2016/17
2° year of course - First semester
Professor
Academic discipline
Statistica (SECS-S/01)
Field
Statistico-matematico
Type of training activity
Characterising
42 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in - - -

Learning objectives

The course gives knowledge on basic statistical techniques for Marketing and Management applications.
In particular, the course addresses:
a) Statistical tools for preliminary data analysis and reporting;
b) Descriptive statistical measures;
c) Confidence intervals and hypothesis testing for means and proportions, together with p-value interpretation;
d) Simple linear regression.
The aim of the course is threefold:
1. To provide both a theoretical and a practical understanding of basic statistical methods.
2. To provide a Marketing-driven context for these methods.
3. Using real data and a learning-by-doing approach, to illustrate the application and the interpretation of these methods.
Computational aspects of the methods are addressed through the use of Excel 2013.

Prerequisites

none

Course unit content

The aim of the course is to describe the main basic statistical techniques, with a focus on applications in Marketing and Management. Specifically, the course will address:

a) Statistical tools for preliminary data analysis and reporting;

b) Descriptive statistical measures, for summarizing business information;

c) Confidence intervals and hypothesis testing, for the analysis of sample data;

d) Simple linear regression, which allows the analysis of bivariate relationship and is a prerequisite for more complex statistical modeling.

All these techniques will be applied to business data through Excel 2013.

Full programme

a) Statistical tools for preliminary data analysis and reporting;
b) Descriptive statistical measures, for summarizing business information;
c) Confidence intervals and hypothesis testing, for the analysis of sample data;
d) Simple linear regression, which allows the analysis of bivariate relationship and is a prerequisite for more complex statistical modeling.

Bibliography

M. Riani, F. Laurini, G. Morelli: Strumenti statistici e informatici per applicazioni aziendali. Pitagora Editrice, Bologna, 2013, Chapters 1 – 3.

Teaching methods

Lectures and practical work.

Assessment methods and criteria

Written exam. Knowledge and understanding will be assessed by methodological questions, marked 3 grade points each. The ability of applying knowledge will be assessed by questions on applications and on the use of Excel 2013, marked 3 grade points each. Learning and understanding skills will be assessed by questions on the conclusions to be drawn from basic statistical analysis, marked 3 grade points each.

Other information

Please check professor's web page for updates on course, exams, dates and time, office hours and so on