ANALYTICAL METHODS IN OPERATIONS
cod. 1008738

Academic year 2023/24
1° year of course - Second semester
Professor
- Giorgia CASELLA
Academic discipline
Impianti industriali meccanici (ING-IND/17)
Field
Ingegneria gestionale
Type of training activity
Characterising
48 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ITALIAN

Learning objectives

Knowledge and ability to understand
At the end of the course, the student must have acquired the main knowledge concerning the analytical methods in operations.
Skills
The student must be able to use the most appropriate analytical methods according to the production context and the specific problem to be addressed.
Autonomy of judgment
The student must be able, supported by the results obtained from the application of analytical methods, to evaluate the impact of decisions on process performances.
Communication skills
The student will have to acquire the specific vocabulary concerning the analytical methods in operations. At the end of the course, the student is expected to be able to transmit the main contents of the course in written form.
Learning ability
The student who has attended the course will be able to deepen their knowledge of analytical methods in operations, through the autonomous consultation of specialized texts, scientific or popular magazines, both specific and outside the topics strictly covered in class .

Prerequisites

There are no mandatory prerequisites

Course unit content

1 Introduction to Statistics
1.1 A brief history of statistics
1.2 Data collection and descriptive statistics
1.3 Populations and samples

2 Descriptive statistics
2.1 Organization and description of data
2.1.1 Graphic representations
2.2 The quantities that summarize the data
2.2.1 Sample mean, median and mode

3 The sample distributions
3.1 The sample mean
3.2 The sample variance

4 The variability
4.1 The deviance
4.2 The variance
4.3 Covariance

5 Correlation between variables
5.1 Various types of regression

6 Probability
6.1 Space of results and events
6.2 Axioms of probability
6.3 Principle of enumeration and the binomial coefficient
6.4 Conditional probability
6.5 Independent Events


7 The random distributions
7.1 Bernoulli and binomial distribution
7.2 Poisson distribution
7.3 Normal distribution

Full programme

1 Introduction to Statistics
1.1 A brief history of statistics
1.2 Data collection and descriptive statistics
1.3 Populations and samples

2 Descriptive statistics
2.1 Organization and description of data
2.1.1 Graphic representations
2.2 The quantities that summarize the data
2.2.1 Sample mean, median and mode

3 The sample distributions
3.1 The sample mean
3.2 The sample variance

4 The variability
4.1 The deviance
4.2 The variance
4.3 Covariance

5 Correlation between variables
5.1 Various types of regression

6 Probability
6.1 Space of results and events
6.2 Axioms of probability
6.3 Principle of enumeration and the binomial coefficient
6.4 Conditional probability
6.5 Independent Events


7 The random distributions
7.1 Bernoulli and binomial distribution
7.2 Poisson distribution
7.3 Normal distribution

Bibliography

The slides projected during the course, in PDF format, and all the material used during the lessons and exercises (Excel sheets) are available for the students.
In addition to the shared material, student can personally deepen some topics addressed during the course by referring to the following texts:
• " Probabilità e statistica per l’ingegneria e le scienze " second edition; Sheldon M. Ross - Italian edition edited by Francesco Morandin - APOGEO
• “Statistics for Managers - using Microsoft Excel” seventh edition; David M. Levine, David F. Stephan, Kathryn A. Szabat - PEARSON

Teaching methods

The course has a weight of 6 CFU, which correspond to 48 hours of lessons. The didactic activities will be conducted by lectures alternated with exercises. During the lectures the topics of the course are dealt with from a theoretical-design point of view, in order to favour a deep understanding of the issues.
During the exercises carried out in the classroom, students will be required to apply the theory to an exercise, a real case study or a project developed according to the methodological criteria illustrated in the lessons and in the bibliographic and teaching material.
To complement the teaching methods described so far, if conditions allow, seminars are organized by managers of multinational companies who report concrete experiences gained in real case studies.
The slides and notes used to support the lessons will be uploaded at the beginning of the course on the Elly platform. To download the slides from Elly, you need to register for the online course.
Notes, transparencies, spreadsheets, tables and all shared material are considered an integral part of the teaching material. Non-attending students are reminded to check the teaching material available and the information provided by the teacher through the Elly platform, the only communication tool used for direct teacher / student contact.

Assessment methods and criteria

Verification of learning involves:
- a written test.
The final grade is calculated by assigning each question a rating from 0 to 30 and making the weighted average of the individual assessments, with final rounding up; the test is passed if it reaches a score of at least 18 points. Honors are awarded in the case of achieving the maximum score on each item to which the mastery of the disciplinary vocabulary is added.

Other information