# Introduction to statistics (2009/2010)

### Course not running

Course code
4S00385
Credits
10
Coordinator
Marco Minozzo
Other available courses
Other available courses
SECS-S/01 - STATISTICS
Language of instruction
Italian
Teaching is organised as follows:
Activity Credits Period Academic staff Timetable
1 - lezione 8 2nd semester Marco Minozzo
2 - esercitazione 2 2nd semester Annamaria Guolo

### Learning outcomes

The course provides to students in economic and business sciences an introduction to probability and to descriptive and inferential statistics.
Prerequisite to the course is the mastering of a few basic mathematical concepts such as limit, derivative and integration at the level of an undergraduate first year introductory course in calculus.

### Syllabus

Descriptive Statistics: data collection and classification; data types; frequency distributions; histograms and charts; measures of central tendency; arithmetic mean, geometric mean and harmonic mean; median; quartiles and percentiles; fixed and varying base indices; Laspayres and Paasche indices; variability and measures of dispersion; variance and standard deviation; coefficient of variation; moments; Pearson’s and Fisher’s indices of skewness and kurtosis; multivariate distributions; scatterplots; covariance; variance of the sum of more variables; method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficiente; deviance residual and deviance explained; multivariate frequency distributions; conditional distributions; measures of association; chi-squared index of dependence; index of association C; Simpson’s paradox.

Probability: events, probability spaces and event trees; combinatorics; conditional probability; independence; Bayes theorem; discrete and continuous random variables; distribution function; expectation and variance; Markov and Tchebycheff inequalities; discrete uniform distribution; Bernoulli distribution; binomial distribution; Poisson distribution; geometric distribution; continuous uniform distribution; normal distribution; exponential distribution; multivariate discrete random variables; joint probability distribution; marginal and conditional probability distributions; independence; covariance; correlation coefficient; linear combinations of random variables; average of random variables; sum of normal random variables; weak law of large numbers; Bernoulli’s law of large numbers for relative frequencies; central limit theorem.

Inferential Statistics: sample statistics and sampling distributions; chi-square distribution; Student-t distribution; Snedecors-F distribution; point estimates and estimators; unbiasedness; efficiency; consistency; estimate of the mean, of a proportion and of a variance; confidence intervals for a mean for a proportion (large samples) and for a variance; hypothesis testing; one and two tails tests for a mean, for a proportion (large samples) and for a variance; hypothesis testing for differences in two means, two proportions (large samples) and two variances.

The course consists of a series of lectures (64 hours) and of ten exercise classes (20 hours).
All classes are essential to a proper understanding of the topics of the course.

### Assessment methods and criteria

For the official examination both written and oral sessions are mandatory.
The course is considered completed if the candidate has done the written test and passed the oral exam.
Students that has received at least 15 out of 30 in the written exam are allowed to attend the oral exam.

 Activity Author Title Publisher Year ISBN Note 1 - lezione M. R. Middleton Analisi statistica con Excel Apogeo, Milano 2004 Testo di approfondimento. 1 - lezione F. P. Borazzo, P. Perchinunno Analisi statistiche con Excel Pearson, Education 2007 Testo di approfondimento. 1 - lezione S. Bernstein, R. Bernstein Calcolo delle Probabilita', Collana Schaum's, numero 110. McGraw-Hill, Milano 2003 Testo di approfondimento. 1 - lezione D. OLIVIERI Fondamenti di statistica (Edizione 3) Cedam, Padova 2007 Libro di testo. 1 - lezione D. OLIVIERI Istituzioni di statistica CEDAM 2005 Testo di approfondimento. 1 - lezione E. Battistini Probabilità e statistica: un approccio interattivo con Excel McGraw-Hill, Milano 2004 Testo di approfondimento. 1 - lezione D. Piccolo Statistica Il Mulino 2000 8815075968 Testo di approfondimento. 1 - lezione S. Bernstein, R. Bernstein Statistica descrittiva, Collana Schaum's, numero 109 McGraw-Hill, Milano 2003 Testo di approfondimento. 1 - lezione S. Bernstein, R. Bernstein Statistica inferenziale, Collana Schaum's, numero 111. McGraw-Hill, Milano 2003 Testo di approfondimento. 1 - lezione D. Piccolo Statistica per le decisioni Il Mulino 2004 8815097708 Testo di approfondimento. 1 - lezione D. OLIVIERI Temi svolti di statistica (2001-2007) Cedam, Padova 2008 Testo di approfondimento.
 Title Format (Language, Size, Publication date) 01) Informazioni sul corso pdf (it, 55 KB, 23/02/10)

#### Statistics about transparency requirements (Attuazione Art. 2 del D.M. 31/10/2007, n. 544)

 Outcomes Exams Outcomes Percentages Average Standard Deviation Positive 35.12% 23 3 Rejected 18.86% Absent 30.08% Ritirati 15.60% Canceled 0.32%
 18 19 20 21 22 23 24 25 26 27 28 29 30 30 e Lode 9.7% 11.1% 7.8% 11.1% 7.8% 12.0% 10.6% 7.8% 6.9% 6.4% 3.2% 1.8% 1.3% 1.8%

Data from AA 2009/2010 based on 615 students. I valori in percentuale sono arrotondati al numero intero più vicino.