The course is divided into the following points:
• Collection, organization and description of data through frequency distributions, graphic representations and synthetic indices of position and variability.
• Study of the relationship between two characters through double entry tables, dispersion diagrams, dependence indicators (such as covariance, the linear correlation coefficient) and linear interpolation.
• Statistical inference, statistical population, sampling, sample variability and main statistics.
• Theory of point and interval estimation.
• Tests hypotheses with particular attention to population mean or relative frequency

Statistical data
Sources

Direct and indirect survey. Survey phases. Polls
Source of data of interest for management
Organising the information and graphical representations

Absolute and relative frequency distributions
Graphical representations of frequency distributions
Categorical variables and numerical variables
Cumulative distribution and its graphical representation
Statistical ratios and index numbers.
Position and variability indices
Position indices for categorical variables
Mode
Median and quantiles
Position indices for numerical variables
Range
Interquantile difference
Variance and standard deviation
Coefficient of variation
Standardised numerical variables and linear transformations. Uses of management interest
Other shape indices
Comparison of different variables of interest for management, using position and variability indices. Box-plot
Bivariate distributions
Relations between two variables
Data organisation
Contingency tables, joint distribution, marginal distirbutions, conditional distributions
Association and correlation between variables
Association for categorical variables
Chi-square related association coefficient
Introduction to ontingency analysis
Uses of management interest
Correlation for numerical variables
Graphical representations
Covariance
Correlation
Uses of management interest
Introduction to probability
Historical remarks
Random experiments, events and probability
Set operations. Probability of intersection and union of events
Conditional probability
Independence between events
Bayes' Theorem
Total probability theorem
Uses of management interest
Random variables
Discrete random variables and related indices
Continuous random variables and related indices
Cumulative distribution functions
Joint distributions between discrete random variables
Bernoulli, binomial and geometric distributions. Uses of management interest
Uniform, exponential and normal distributions. Uses of management interest
Introduction to statistical inference
Basic ideas in statistical inference
Sampling and sampling distributions
Point estimate of population mean and proportion
Interval estimate of population mean and proportion