Mathematics and statistics

A.Y. 2017/2018
10
Max ECTS
108
Overall hours
SSD
MAT/02 SECS-S/01
Language
Italian
Learning objectives
Knowledge of the basics of Maths, in particular, of elementary Calculus (real functions in one variable, limits, derivatives, integrals).
Knowledge of descriptive statistics. Position and variability indices. Acquisition of the principles and the techniques of regression and correlation between variables. Knowledge of inferential statistics. Analysis of Variance.
Knowledge of the basics of Maths, in particular, of elementary
Calculus (real functions in one variable, limits, derivatives,
integrals).
Knowledge of descriptive statistics. Position and variability indices.
Acquisition of the principles and the techniques of regression and
correlation between variables. Knowledge of inferential statistics. Analysis of Variance.
Expected learning outcomes
Possibility of exploiting the basic tools of Maths in any context.
Describe phenomena using main statistical indicators. Plan sampling surveys. Using the one and two-ways analysis of variance. Objective assessment of statistical surveys results.
Possibility of exploiting the basic tools of Maths in any context.
Describe phenomena using main statistical indicators. Plan
sampling surveys. Using the one and two-ways analysis of
variance. Objective assessment of statistical surveys results.
Course syllabus and organization

Single session

Responsible
Lesson period
First semester
Mathematics
Course syllabus
Numerical sets.: N, Z, Q e R. The coordinate plane:
straight lines, parabolas, circles. Outline of trigonometry.
Elementary functions and their graph. Equations,
inequalities and system of algebraic and irrational
inequalities. Generalities about real funcion: domain,
range, injective and surjective functions, composed
functions, inverse functions, geometric transforms of
elementary functions. Limits: computing limits,
comparison of infinites and infinitesimals, indeterminate
forms. Continuity. Asymptotes: vertical, horizontal and
slant. Differential calculus: first derivative, tangent line,
monotonicity, global and local maxima and minima.
Second derivative: convexity and concavity, inflection
points. Integral calculus. Computation of plane areas.
Teaching methods
agrimat e matematica assistita reperibile al link
http://ariel.ctu.unimi.it/corsi/mateassistita
Statistics
Course syllabus
1- The language of statistics.
2- Organization of data end graphical representation.
3- Position and variability indices (mean, mode, median),
variance.
4- Bivariate analysis for qualitative or quantitive data.
5- Probability, probability rules. Independents events. Total
probability theorem. Bayes theorem.
6- Random variables, distributions. Distributions: binomial,
geometrical, Poisson, Gaussian.
7- Random samples. Confidence intervals. Estimation. Sample
mean. Central Limit Theorem. Confidence interval for the mean.
8- Hypothesis tests: fundamentals, phases, simple test.
9- Hypothesis test on a single population proportion.
10- Test and confidence interval for the difference of two means
using independent sample.
11- Correlation analysis. Univariate linear regression. Inference.
12- Analysis of variance.
Teaching methods
Introduzione alla Statistica, di M.K. Pelosi e T.M. Sandifer, ed.
McGraw-Hill, 2009.
Mathematics
MAT/02 - ALGEBRA - University credits: 6
Practicals: 40 hours
Lessons: 28 hours
Professor: Poggioli Daniela
Statistics
SECS-S/01 - STATISTICS - University credits: 4
Practicals: 16 hours
Lessons: 24 hours
Professor: Baldi Lucia
Professor(s)
Reception:
on appointment
Via Celoria 2, Milan, Italy, 3rd floor (or by Skype/Teams/Zoom)