CORPORATE STATISTICS AND DATA ANLYSIS
Learning outcomes of the course unit
a) Knowledge and understanding
The course allows students to acquire advanced level knowledge and understanding of business and management issues focusing on applied problem solving, in particular:
- Knowledge of the main sources of official Italian data (ISTAT, ISMEA, etc..)
- Knowledge of inductive methods of inferential statistics for the specification, estimation and testing of parameters of statistical models used in forecasting and decision-making and in auditing
- Acquisition of key statistical tools for decision making and quality management.
b) Ability to apply knowledge and understanding
At the end of the course, students will be able to measure, detect and process economic data also through the use of appropriate software. Students will be able to design and manage surveys, to contribute to problem solving with reference to economic contexts.
At the end of the course, students will be able to set up a statistical survey from the data collection, through the preparation of sampling plans, to the quantitative analysis. Students will be able to assess the implications and results of the business activities.
d) Communication skills.
At the end of the course, students will be able to interact with all levels of a company, delivering results in terms of quantitative summaries of company information and correctly interpreting the results of sample analysis.
e) Ability to learn (learning skills).
The course will stimulate the student towards a critical reflection on the principles of construction / utilization of information and on the application of statistical methods to business issues.
Students are expected to know the basic elements of descriptive and inferential statistics from a course in Basic Statistics
Course contents summary
The course aims to provide students with the tools for the analysis of company decision-making and management, inevitably treated under conditions of uncertainty and risk, and therefore requiring statistical methods as scientifically rigorous support. Particular attention is paid to sampling techniques for statistical control of book values and procedures for the estimation of accounting estimates in the review and certification of financial statements. Other topics include the multiple linear regression model for forecasting and statistical quality and productivity control.
This basic theory is necessary to understand the aware use of the methods and results. The course also covers applications and aspects of computing, with the use of Excel and SPSS software.
Developing competences and learning outcomes
1) Introductory Concepts - Statistical information for business
2) Types of sampling methods: probability and nonprobability samples
3) The multiple linear and logistic regression model for statistical forecasts
4) Statistical applications in quality control and process capability
5)Evaluation of the companies economic and financial performance.
Luigi Biggeri, Matilde Bini, Alessandra Coli, Laura Grassini, Mauro Maltagliati, Statistica per le decisioni aziendali, Pearson, Milano, 2012, (Chapters 1, 2, 4, 6).
Supplementary exam preparation material can be downloaded from: http://economia.unipr.it/docenti/milioli
Acquisition of knowledge: lectures
Acquisition of the ability to apply knowledge: Exercises
Acquisition of independent judgment: During the course students will be encouraged to identify strengths and weaknesses of the discussed methods
Acquisition of learning skills: for each topic the description of problems to solve is followed by critical analysis of the solution
Acquisition of technical language: The course covers the meaning of statistical terms for proper use in business.
Assessment methods and criteria
Written exam of 75 minutes, consisting usually of 4 or 5 exercises containing separate questions. Each exercise carries a maximum number of marks.
Questions cover the entire syllabus, both about theoretical and practical aspects. They aim to assess ability to understand, independence of judgment, and ability to use appropriate terminology and language. The wide range of issues covered by the questions ensures that both learning ability and the ability to apply knowledge are tested.