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Contents of the basic courses of Mathematics and Statistics.
The course develops the key concepts of statistical inference and the main methods of sampling theory to be used in supporting managers and business decision-makers. Preliminary elements of probability theory and random variables used within problems involving choices under uncertainty are also treated and empirical applications are presented as well as some topics of classical and modern time series analysis.
- Main theorems of Probability and more important Random Variables. - Population and sample. - Parameters of the population. - Probability and non-probability samples. - Statistics, Estimators, Estimates. - Sampling Distribution of the estimators. - Properties of an Estimator. - Confidence Intervals and precision of estimates. - Fundamentals of Statistical Hypothesis. - Strategies and Sample Design Effect; Sample Size. - Plans of probabilistic and non-probabilistic Sampling. - Sampling for auditing. - Analysis of classical and modern time series. - Simple and Multiple Regression Models. - Tests of Independence.
- Levine D.M., Krehbiel T.C., Berenson M.L. (2010), Business Statistics, Pearson Education, New Jersey
More information will be given during the course.
The course consists of theoretical lessons with examples in economics and business and is supported by a course with exercises, some of which to do in Computer Lab.
Examination includes a written test and an oral test that will take place in the same exam session. The tests will cover all the topics of the course. The written test may be conducted in two parts: mid-term exam (at the end of the first two months) and final exam (at the end of the second two months of teaching). The evaluation of any audits online (performed during the course) will be able to integrate the written test.