The course aims at providing the knowledge needed to collect and analyse useful data for business management, supporting the decision-making process within a firm. In a business environment that needs to analyse increasing amounts of data, the application of appropriate statistical methods to business data provides information supporting management decisions. The course intends to discuss the rationale behind the application of statistical methods to business data and to explain their application fields. On these premises, topics are introduced by considering the information needs that can be met through statistical methods, focusing on the reasons for applying statistical tools to practical cases. The definition of the data describing a business concept and the selection of the relevant data source are necessary to meet the information needs above. By the end of the course, students are expected to acquire: - the knowledge of the data sources that can be used to meet information needs; - the knowledge of the statistical methods for business analysis, according to available data and information needs; - the ability to apply univariate and multivariate statistical methods to data; - the ability to interpret results and provide information supporting management decisions.
Data sources and statistical information for business:
- primary and secondary data
- internal and external sources of data
- probabilistic sampling for market survey
Economic and business indicators:
- simple and composite index numbers
- turnover rates
- measures of productivity variation
- transition matrices and career transition measures
- smoothing techniques: moving averages and exponential smoothing
- techniques for decomposing economic time series applied to business forecasting
Introduction to statistical quality control:
- process capability ratios
- analysis of variance
- control charts for variables
Multivariate statistical analysis for business data and company business performances:
- simple linear regression models
- multiple linear regression models
- logistic regression models
- principal components analysis on accounting ratios
- cluster analysis
Lecture slides and other learning materials are available on the e-learning website.
|Biggeri Luigi , Matilde Bini , Alessandra Coli , Laura Grassini , M. Maltagliati||Statistica per le decisioni aziendali. Ediz. mylab. Con eText||Pearson Education Italia||2012||9788891902764|
The assessment of learning outcomes consists in a written examination.
The written examination assesses the level of knowledge of the course topics, the ability to apply statistical methods for business and the interpretation of results.
Structure of the examination
The examination consists of multiple choice questions, questions which requires a numerical response, and open-ended questions. All kinds of questions may be focussed on theoretical and methodological issues, may consist in exercises, or may require the student to discuss and analyse some practical problem using notions and tools learned throughout the course.
All students getting a grade equal to or larger than 15/30 are allowed to take an optional oral examination which completes the evaluation of the acquired knowledge. The final grade may be equal, higher or lower than the grade got on the written part of the exam.
The examination score is on a 30-point scale (passing mark: 18).