2020/2021

2020/2021

DM270

SECS-S/01 (STATISTICS)

DEPARTMENT OF ECONOMICS AND MANAGEMENT

BUSINESS ADMINISTRATION, CONTROL AND CORPORATE FINANCE

PERCORSO COMUNE

1°

(22/02/2021 - 22/05/2021)

9

66 lesson hours

Italian

WRITTEN TEST

TARANTOLA CLAUDIA - 9 ECTS

There are no formal prerequisites. Nevertheless, it is suggested to have a sufficient knowledge of the main topics of the general math course.

The course explores techniques for collecting and analysing real data. The main aspects of statistical thinking, both descriptive and inferential, are presented together with the fundamentals of probability theory and random variables.
The aim of the course is to provide students with the models and main statistical tools useful to the understanding and solution of economics and business problems.


Intended Learning Outcomes

Knowledge and understanding
At the end of the course students will be able to understand the different types of data and to provide a descriptive summary of the data by means of synthetic indicators. Furthermore, he will be able to solve simple inferential problems, through appropriate statistical models.

Applying knowledge and understanding
At the end of the course students will be able to appropriately summarize the data, estimate unknown parameters of the examined population and perform hypotheses testing by means of sample data, construct simple statistical models to study the relationships between relevant variables.

1. Data analysis:
• qualitative and quantitative data;
• statistical distributions and graphical representations;
• location indices: mean, mode, median and quantiles;
• variability: variation range, interquartile range, variance, coefficient of variation;
• Chebychev inequality;
• double distributions: covariance and linear correlation coefficient;
• linear relationships: the regression line.
2. Probability:
• Introductory concepts: definition of probability and some of its basic properties;
• conditional probabilities and independent events. Bayes' theorem;
• random variables;
• expected value, variance and moments of a random variable;
• probability distributions, in particular: Bernoulli, Binomial, Poisson, normal
• joint distribution of two random variables.
3. Statistical inference:
• population, sample, statistics and parameters;
• sampling distributions;
• central limit theorem;
• estimate;
• interval estimation;
• hypothesis testing;
• Simple linear regression.

•Face-to-face lectures
•In-class exercises
•Exercises based on the electronic platform mymathlab.it of the textbook
• Suggested exercises will be uploaded on the platform KIRO on a weekly base. These exercises should be carried out individually by the students. They will be solved during the tutorial of the following week.
•Team project (optional)

P. Newbold, W.L.Carlson, B. Thorne (2010).
Statistics for Business and Economics. Paerson.

A written general exam or two partial written exams (one in the middle and one at the end of the course).
The first partial exams consists of multiple choice questions
The second partial exam consists of open ended questions
The general exam consist of multiple choice questions and open ended questions.

Team project (optional)