Introductory economics and statistics

A.Y. 2020/2021
Overall hours
Learning objectives
The aim of the course is to introduce students to jargon and basic principles of economics and statistical sciences. The module of Economics is meant to explain laws describing behavior and interaction among economic agents (families and firms) mainly at micro level (microeconomics) with a short outline at aggregated level (macroeconomics). The module of statistics introduces descriptive statistics and treats some topics of inferential statistics.
Expected learning outcomes
Students will be able to understand and manage economic information concerning issues on supply and demand of agri-food and catering markets, reported both by newspapers and by economics and food science reviews. Students will be able to correctly understand and represent statistical data both in tabulation and in diagram.
Course syllabus and organization

Single session

Lesson period
Second semester
Teaching methods: The lessons, held using the Microsoft Teams platform, can be followed both in synchronous and asynchronous way. All lessons will be recorded and made available to students.
Program and reference material: will not change.
Learning assessment procedures and assessment criteria: The content of the test will not change. The (written) exam will take place remotely, using the ExamNet platform. The student surveillance will be carried out by teachers through the Microsoft Teams platform.
Course syllabus
Chapter 1. Introducing Economics - What do economists study? Different economic systems. The nature of economic reasoning. Chapter 2. Supply and Demand - Demand. Supply. Price and output determination. The control of prices. Chapter 3. Markets in Action - Elasticity. The time dimension. Agriculture and agricultural policy. Chapter 4. Background to Demand - Marginal utility theory. Indifference analysis. Chapter 5. Background to Supply - The short-run theory of production. Costs in the short run. The long-run theory of production. Costs in the long run. Revenue. Profit maximization. Chapter 6. Profit Maximising Under Perfect Competition and Monopoly - Alternative market structures. Perfect competition. Monopoly. The theory of contestable markets. Chapter 7. Profit Maximising under Imperfect Competition - Monopolistic competition. Oligopoly. Game theory. Price discrimination.

Language of statistics. Graphical representation of data. Numerical description of data. Bivariate data analysis. Probability. Random variables and probability distribution. Confidence intervals, hypothesis testing. Test on a single population. Test on two populations.
Prerequisites for admission
Basic knowledge of linear algebra and analytic geometry. The attendance of the course of mathematics and the preparation of the relative test are strongly recommended.
Teaching methods
The teaching method involves lectures and classroom exercises. Moreover, targeted exercises, managed and programmed by the teacher, are also proposed using web-platforms connected to the reference texts. These exercises must be carried out during the course, within defined dates. When the correct answers are more than the 70% of total questions, the student obtains up to 3 points more on the final grade (which must however be sufficient).
Teaching Resources
Economics: Sloman, J., Wride J, Garrat D. Economics, Pearson.
Statistics: Pelosi M. K. e Sandifer T. M. (2009). Elementary statistics from Discovery to Decision, McGraw-Hill.
Assessment methods and Criteria
Student assessment about the Elements of Economics and Statistics learning comes from a final written exam. Specifically, a single test of about 30 true/false questions, 30 multiple choice questions, three exercises (2 in statistics, 1 in economics) and an open question (economy) is proposed. The test is performed in a maximum time of 90 minutes. The test takes into account all the course's program. The days of tests are communicated at the beginning of the course and fixed through the University application (SIFA).
Practicals: 16 hours
Lessons: 56 hours
Professor: Raimondi Valentina