•GUIDA ECONOMIA 07-08 - Università degli studi di Udine

242 prospectus udine
- P. BORTOT, L. VENTURA, A. SALVAN,
Inferenza Statistica: applicazioni con S-
PLUS e R, Cedam, Padova, 2000.
Further reading
- G. CICCHITELLI, Probabilità e Statistica,
second edition, Maggioli Editore, 2001.
- S. IACUS, G. MASAROTTO, Laboratorio di
Statistica con R, McGraw-Hill, 2003.
STATISTICS
CdL BE, EBA)
Prof.ssa Laura Pagani
(CdL BF, EC)
Prof. Enrico Gori
Contents
Probability and statistics are branches of
applied mathematics. Business uses
them to quantitatively describe many
events and processes. Therefore, a practical
knowledge of probability and statistics
is valuable in many aspects of business.
The aim of this course is to teach the
basic principles of the most common statistical
techniques used in business. A
basic knowledge of mathematics is necessary
to understand the concepts. However,
the course emphasizes the practical
use of these concepts to solve real business
problems.
1. Descriptive statistics: a summary.
2. Introduction to probability: experiments,
events and their probability, conditional
probability, Bayes’ theorem.
3. Discrete random variables: discrete
probability distributions, expected value
and variance, binomial and poisson probability
distributions. Continuous random
variables: probability density function,
expected value and variance, exponential
and normal probability distributions.
4. Linear combination of random variables;
central limit theorem.
5. Sampling and sampling distributions:
simple random sampling, introduction to
sampling distributions, sampling distribution
of the sample mean, sampling distribution
of the sample proportion: largesample
case, sampling distribution of the
difference between the means of two populations:
Independent samples, smallsample
case (the normal population) and
large-sample case; sampling distribution
of the difference between the proportions
of two populations: large-sample case.
6. Point estimation: point estimators,
properties of point estimators: unbiasedness,
efficiency, consistency.
7. Interval estimation: interval estimation
of a population mean: small and large
sample case. Interval estimation of a population
proportion: large-sample case;
interval estimation of the difference
between the means of two population:
independent samples, small-sample case
(the normal population) and large-sample
case; interval estimation of the difference
between the proportions of two populations:
large-sample case. Determining
the sample size.
8. Hypothesis testing: developing null
and alternative hypotheses; type I and II
error, tests on a population mean: smallsample
case (one-tailed and two-tailed
tests), the normal population; tests on a
population mean: large-sample case (onetailed
and two-tailed tests); tests about a
population proportion: large-sample case
(one-tailed and two-tailed tests); hypothesis
tests on the difference between two
means of two populations: large and
small-sample size; tests on the difference
between the proportions of two populations:
large-sample size.
9. Introduction to simple linear regression.
Bibliography
- S. BORRA, A. DI CIACCIO, Statistica,
Metodologie per le scienze economiche e
sociali, McGraw-Hill, Milano, 2004.
- D. PICCOLO, Statistica per le decisioni, Il
Mulino, Bologna, 2004.