Business Statistics
A.Y. 2020/2021
Learning objectives
The course of Business Statistics aims to provide the knowledge of the main Data Mining techniques addressed to the analysis of business data. Indeed, the increasing availability of data, typically generated by the information society, has brought out the need to deal with methodologies and tools for the quantitative decision-making processes in economic and business applications. Data may have source within the firm, such as those related to customers or users, or may derive from appropriate market researches. The presence of data of different nature (i.e., both qualitative and quantitative) requires that the student achieves suitable skills which allow him to justify the logical process underlying the adoption of a specific technical analysis, to formulate a reasoning in a critical and rigorous way and to detect the synthetic information to support decisions especially in the risk management process.The skills achieved in the course of Business Statistics will be useful for the courses whose main issues are related to marketing, market research and decision-making processes.
Expected learning outcomes
At the end of the course the student will have achieved the skills for the theoretical and practical formalization of the Data Mining techniques presented along the course. In particular, the student will be able to: recognize the differences between supervised methods, non-supervised methods, descriptive models and predictive models; demonstrate an adequate ability to choose the most suitable model based on the features of the available data and the purpose of the analysis to be led; select, among several models, the model characterized by the greatest predictive accuracy; implement the models using the programming language of the statistical R software; correctly interpret the analysis outputs by extracting information that can support the decision-making processes.
Lesson period: Third trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Third trimester
Depending on the progress of the pandemic contagiousness, if necessary, the course will be held remotely with synchronous lessons through the Microsoft Teams platform.
The exam will take place remotely using exam.net in the case of a written exam or Microsoft Teams in the case of an oral exam. The professor will indicate in ARIEL the type of exam chosen.
The exam will take place remotely using exam.net in the case of a written exam or Microsoft Teams in the case of an oral exam. The professor will indicate in ARIEL the type of exam chosen.
Course syllabus
The topics of the Business Statistics course are mainly focused on:
- Presentation of information available within a company and statistics external to the company (such as the main statistical information disseminated by Istat and individuals);
- Macroeconomic accounting, the structural characteristics of the production system, the economic results;
- Presentation of the characteristics and main designs of the sample surveys;
- Elementary rules and tools for making correct comparisons (methods of elimination or decomposition; statistical derivation ratios; synthetic index numbers);
- Presentation of the permanence rates and the relative transition matrices for the evaluation of career development;
- Statistical quality control to ensure the survival and success of a company (offline and online methods);
- Study of the ANOVA method and control chart for variables;
- Statistical methods for evaluating the technical performance of the production process (variation in partial or total productivity);
- Hicks-Moorsteen and Malmquist approach;
- Presentation of information available within a company and statistics external to the company (such as the main statistical information disseminated by Istat and individuals);
- Macroeconomic accounting, the structural characteristics of the production system, the economic results;
- Presentation of the characteristics and main designs of the sample surveys;
- Elementary rules and tools for making correct comparisons (methods of elimination or decomposition; statistical derivation ratios; synthetic index numbers);
- Presentation of the permanence rates and the relative transition matrices for the evaluation of career development;
- Statistical quality control to ensure the survival and success of a company (offline and online methods);
- Study of the ANOVA method and control chart for variables;
- Statistical methods for evaluating the technical performance of the production process (variation in partial or total productivity);
- Hicks-Moorsteen and Malmquist approach;
Prerequisites for admission
In order to adequately understand the contents of the course, the students must have basic knowledges in Statistics and Mathematics.
Teaching methods
The course will be organized through lectures with support tools consisting in the employment of the overhead projector, through which the mathematical passages underlying models and methodologies will be illustrated.
Teaching Resources
The main reference books for the preparation of the exam are indicated below.
- Material available on the website of the course;
- Statistica per le decisioni aziendali by Luigi Biggeri, Matilde Bini, Alessandra Coli, Laura Grassini, Mauro Maltagliati (editor Pearson)
- Material available on the website of the course;
- Statistica per le decisioni aziendali by Luigi Biggeri, Matilde Bini, Alessandra Coli, Laura Grassini, Mauro Maltagliati (editor Pearson)
Assessment methods and Criteria
Final Written Exam. The exam will be divided in two parts:
-) multiple choice questions;
-) open question/solve exercises
At the exam, you can bring a A4 paper (both sides) with formulas.
-) multiple choice questions;
-) open question/solve exercises
At the exam, you can bring a A4 paper (both sides) with formulas.
Professor(s)
Reception:
Each Wednesday 10 -12
DEMM, room 31, 3° floor (By appointment, please send an email)