STATISTICS FOR DATA ANALYSIS

Single discipline educational activity

Course Sheet

Course code:

STANDA18

Academic Year of enrolment:

2021

Year of supply:

2021/2022

Type of Course:

Characterising

Degree:

Course of 2nd Cycle Degree in MANAGEMENT AND ECONOMICS

Disciplinary Sector:

Statistics

Language:

Italian

Location:

PESCARA

Credits:

Programme Year:

Professor and Collaborators:

RAPPOSELLI AGNESE

Cycle:

Second four months

Hours of classroom activity:

Individual study hours:

171

Prerequisites:

Although no prerequisites are required, knowledge of the basic concepts of both descriptive and inferential statistics is recommended.

Objectives

The course pursues the general objective of the master degree, and more specifically of the "Professional accounting and Business Consulting" and “Management” specializations, to provide knowledge and skills regarding the strategic dynamics of companies, the indicators and the approaches useful for the evaluation of firms performance and for the estimation of companies economic value, the processes used for financial statements audits, as well as to provide knowledge and skills useful for understanding the strategic and competitive context where firms operates, the innovation and value creation processes.
To this purpose, the course aims to convey advanced knowledge and skills in the quantitative field, in order to favor the correct reading and interpretation of business data to support the company decision-making process. More specifically, the course aims at providing knowledge to collect useful data for business management and to apply appropriate statistical methods for business in order to support management decisions and evaluation and auditing processes.

At the end of the course the student must possess knowledge and skills related to the collection and organization of business data, their analysis by means of appropriate statistical methods for business and the presentation and interpretation of results obtained.
The objective is to contribute to the formation of a professional profile (envisaged in the master degree, more specifically in the "Professional accounting and Business Consulting" and “Management” specializations) with high technical and professional skills in the areas of auditing, firms performance evaluation and business consultancy, as well as in the areas of management of innovation, entrepreneurship and marketing processes. To this end the course proposes to transmit the following skills and knowledge:
KNOWLEDGE AND UNDERSTANDING ABILITY

- in-depth and specialized knowledge for the collection and organization of business data;
- knowledge of the statistical methods for business analysis, according to available data and information needs;
- the ability to interpret the results obtained and provide information supporting management decisions.

To this end the course proposes to transmit the following skills and knowledge in terms of specific objectives:
KNOWLEDGE AND UNDERSTANDING (applied)
- the knowledge of the data sources that can be used to meet business information needs;
- the ability to apply univariate and bivariate statistical methods to business data;
- the ability to apply multivariate statistical methods to business data, in particular the multiple linear regression model, the logistic regression, principal components analysis;
- the ability to apply parametric and non-parametric methods for measuring firms efficiency, such as DEA and SFA;
- the ability to apply the acquired knowledge for the diagnosis and understanding of business phenomena.

AUTONOMY OF JUDGMENT:
- ability to independently choose the most suitable type of analysis based on the reference context and the type of data available;
- ability to interpret the results obtained autonomously through an advanced statistical analysis;
- ability to convey in oral form analytical and summary considerations on the basic principles of the discipline and to make interdisciplinary connections.
COMMUNICATION SKILLS:
- to use the appropriate statistical terminology;
- to communicate the results of a statistical analysis based on the objectives to be pursued and the recipient of the report.
LEARNING ABILITY:
- to carry out individual and group research on specific aspects of the subject;
- to compare own skills with the most recent approaches
(tools: other supporting material, texts, group exercises)

Contents

The course is divided into three main modules.
A) Data sources and statistical information for business decisions. Organisation of the data. Data matrix. Descriptive statistics for analysing business data.
B) Multivariate statistical analysis for business data and company business performances.

C) Measures of firm efficiency. Frontier analysis methods.

Extended Syllabus

A) Data sources and statistical information for business decisions:
- primary and secondary data;
- internal and external sources of data.
Organisation of the data.
Data matrix.
Descriptive statistics for analysing business data:
- univariate exploratory analysis on accounting data;
- bivariate exploratory analysis of quantitative data. Correlation between business variables.
Simple linear regression model.
B) Multivariate statistical analysis for business data and company business performances:
- multiple linear regression model;
- case study: multiple linear regression model for analysing business performances;
- logistic regression;
- case study: logistic regression for predicting firm financial distress;
- principal components analysis (PCA);
- case study: principal components analysis on accounting ratios.

C) Measures of firm efficiency. Frontier analysis methods:
- different approaches to efficiency measurement;
- parametric methods: Stochastic Frontier Analysis (SFA);
- non-parametric methods: Data Envelopment Analysis (DEA);
- Firms businesses performances evaluation: case studies.

Recommended Bibliography

Bracalente B., Cossignani M., Mulas A. (2009). Statistica aziendale. Mc-Graw-Hill, Milano.
Other supporting material provided by teacher will be available on the e-learning page.

Methods of Provision

Conventional

Teaching Methods

The course includes 54 hours of lessons divided into 3 weekly lessons (one lesson of 2 hours and two lessons of 2 hours) and will be organized in three modules of frontal lessons, exercises, case studies.

Frequency is recommended.

Evaluation methods

Verification of learning:

The assessment of the learning level will be carried out with the use of a written test.

The written examination consists of: i) both open and multiple choice questions about topics covered during the course; ii) exercises in which students are asked to solve real case-studies using statistical methods presented during the course.
This test must be solved in one hour and a half and is aimed at probing above all "the knowledge" and the "know-how" (Dublin Descriptors 1 and 2). In particular, the exam is aimed at verifying the understanding of the topics covered, the student’s ability to apply statistical methods for business data analysis and to interpret the results obtained.
The exam score is on a 30-point scale.

The examination procedures are the same for attending and non-attending students.

Contacts/More Information

All information concerning the course and other learning materials will be available on the e-learning page.
Erasmus students must contact the teacher for their program. They can take their exam in English or in French (written and oral exam).

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

Aree