This course will introduce the methods for inferential statistics with applications focusing on finance.
The free-ware statistical software "R" (free version of the commercial software "Splus", one of the main software used for statistical purposes) will be used to perform hypothesis tests and construct confidence intervals building on the knowledge of the software acquired in the Introduction to Statistics course which is a prerequisite of the course.
The software can be downloaded from the website: http://www.r-project.org/.
Data, imported from an Excel spreadsheet into "R", will be analysed from an inferential point of view.
The students will be assumed to have learned, in the course Introduction to Statistics (which is a pre-requisite), the following concepts of probability theory and descriptive statistics. They need further more to know the basics on the free-ware statistical software “R” (also acquired in the Introduction to Statistics course).
Introduction to probability:
definitions, concept of marginal and joint probability, low of total probability, conditional probability, notion of independence
discrete (Bernoulli, Binomial, Geometric, Poisson, Uniform) continuous (Uniform, Gaussian or Normal, Exponential, Student-T, Chi-square)
measure of location (mean, median, mode) and dispersion (variance, std deviation, quantiles)
two way tables, joint and marginal distributions, covariance and correlation
Graphical instruments to visualize data
Details of the course
The course focuses on inferential statistics both theoretical and applied (with a focus on financial applications).
- Theory of point estimation (methods and properties of estimators)
- Construction of confidence intervals
- Theory of hypothesis tests
Lecture notes will be available on the e-learning website
P. Newbold, W. Carlson, B. Thorne. Statistics for Business and Economics, Prentince Hall, 2010. 7th Edition, (also available in Italian).
M.J. Crawley. Statistics: An Introduction using R, Wiley, New York, 2005.