STATISTICS

The course is one of the core educational activities of the Business Administration and Management degree program that allows students to acquire the knowledge and understating of the main statistical concepts used in management disciplines.
The aim of the course is to provide the basic knowledge of descriptive statistics, probability theory and inferential statistics to develop skills that allow them to structure, process and analyze data in order to describe and make inference in problems characterized by uncertainty such as in economics, finance, quality control and marketing.

At the end of the course, students will be expected to have acquired the basic knowledge of statistics to develop descriptive and inferential analyses of business phenomena through tools and statistical methods suitable for the analysis, as for example graphics and numerical synthesis, punctual or interval estimates, hypothesis tests. In particular, students should:
1. Knowledge and understanding
- know the terminology and basic concepts of descriptive and inferential statistics for business phenomena;
- know the basic notion of probability theory;
- understand the strengths and limitations of the statistical approaches used to analyze business phenomena.
2. Ability to apply knowledge and understanding
- know how to determine the best statistical methods for the analysis of real phenomena;
- understand the main aspects of the descriptive and inferential statistical analyses;
- know how to apply the main probabilistic models to business.
3. Making judgements
- be able to critically assess under which circumstances the analyses are reliable;
- be able to assess the goodness of the achieved results.
4. (Lifelong) learning skills
- be able to critically consult reference books and online material in the fields of statistics and analysis of data for business phenomena.

Being clear of OFA requirements.
Students should have knowledge of the basic concepts introduced in the MATHEMATICS - 1 and MATHEMATICS - 2 courses.
Specifically, students should know: systems of linear equalities and inequalities, matrix algebra, interest rates, minima and maxima of functions.
Students should also have a basic knowledge of set theory.

Below the full content of the 6 CFU course:
1. Graphical description of data sets.
2. Numerical description of data sets
3. Probability.
4. Probability distributions and discrete and continuous random variables
5. Sampling and sample statistics.
To support the theoretical knowledges acquired during the course, each topic will be presented by using business examples.

Mandatory texts:
Betty Thorne - Paul Newbold - William L. Carlson, STATISTICA - 9/Ed (2021), Cap. 1-7, Pearson

Additional readings
Anna Clara Monti, STATISTICA. ESERCIZI SVOLTI (2024), Cap: 1-14, 16-19, Pearson
Levine D. M.; Krehbiel T. C.; Berenson M. L. (2010 o 2014). Statistica, Pearson.
Other reading material suggested by the teacher during the course.

The purpose of the exam is to verify that the student has mastered the concepts and tools presented in the lectures.
Specifically, the exam consists of a written test that includes a sufficient number of quizzes and exercises to test the student's understanding of the program covered, each with its own assigned score.
The test will consist of 6 program related quizzes.
In addition, there will be a structured exercise related to the program.
Quizzes and exercises similar to the final exam will be given during both the theory lectures and the exercises.

The exam will be open book (paper materials only), you are allowed to use a calculator (no PC or tablet), the distribution tables and any materials provided in advance by the instructor.

The correct answer to each of the quizzes in the exam test results in a score of 2 point.
The answer to each of the structured exercises can lead to a maximum score of 20 points.
The sum of points available is therefore 32.

Answers to the structured exercises to be considered correct must succinctly present theoretical justifications for what is stated and, if present, report numerical results free of calculation errors

written

A. scores in the 18-22 range will be awarded in the presence of:
- sufficient knowledge and applied understanding with reference to the syllabus;
- limited ability to interpret data and make independent judgments;
- sufficient communication skills, especially in relation to the use of the technical language of statistics;
B. scores in band 23-26 will be awarded in the presence of:
- fair knowledge and applied comprehension skills with reference to the syllabus;
- discrete ability to interpret data and make independent judgments;
- fair communication skills, especially in relation to the use of the technical language of statistics;
C. scores in band 27-30 will be awarded in the presence of:
- good or very good knowledge and applied comprehension skills with reference to the program;
- good or excellent ability to interpret data and make independent judgments;
- fully appropriate communication skills, especially in relation to the use of the technical language of statistics.

The course is based on face-to-face lectures in which the statistical methods of interest are presented, discussed, and illustrated with examples of business problems.
The course includes fifteen lectures in which the basic concepts of descriptive and inferential statistics will be introduced.
In addition, the basics of probability theory will be presented.
Ten exercises devoted to the various contents proposed during the course are also planned.

It is required that students register on the course page of the university e-learning platform moodle.unive.it