Statistics – Bologna

Argomenti del programma: Introduction to data: Data basics; Sampling principles; Experiments and observational studies Summarizing data: Examining numerical data; Considering categorical data Probability: Defining probability; Conditional probability; Bayes theorem Random variables: Discrete and continuous; Expectation; Distributions of random variables: Normal; Geometric; Bernoulli; Binomial Foundations for inference: Point estimates;…

• Educational material (slides and exercises) on the Virtual Learning Environment platform at the link:

Argomenti del programma: Part A — Descriptive Statistics Course introduction and data structures Statistical surveys; populations vs samples; variables and measurement scales; data matrices. Frequency distributions and graphics Univariate tables; histograms, empirical distribution function; cumulative frequencies; statistical ratios; index numbers.

Argomenti del programma: The course program is organized in four parts as described below. 1. Exploratory data analyis Graphical tools for data analysis and presentation. Frequency tables. Frequency distributions. Summary measures of position and dispersion. Two-way contingency tables. Joint, marginal and conditional distributions. Independence and Association. Covariance and correlation. 2.

Argomenti del programma: 1st half Introduction to the R language and the software RStudio. Data frames, observations, variables, computing and interpreting means. Basics of estimating causal effects with randomized controlled trials. Randomized experiment, treatment group, control group. Examples and case studies in R. Difference-in-means estimator. Inferring population characteristics via survey research.

Argomenti del programma: Introduction to data: Data basics; Sampling principles; Experiments and observational studies Summarizing data: Examining numerical data; Considering categorical data Random variables: Discrete and continuous; Expectation; Distributions of random variables: Normal; Geometric; Bernoulli; Binomial Foundations for inference: Point estimates; Confidence intervals; Hypothesis testing Linear Regression

Argomenti del programma: Course structure: The topics of the first part of the course (Module 1) are: Univariate and Bivariate Descriptive Statistics (30 hours). The topics of the second part (Module 2) are: Probability Theory and Statistical Inference (30 hours). Part 1 – EXPLORATORY DATA ANALYSIS (Module 1) Introduction. The data matrix. Type of variables. Frequency tables. Cumulative frequency distribution. Graphical representations.

• Saranno messe a disposizione degli studenti le dispense didattiche relative a tutti gli argomenti del corso.

Argomenti del programma: Statistica descrittiva (classificazione dei dati, valori medi, misure di variabilità e concentrazione, rapporti statistici e numeri indici). Elementi di calcolo delle probabilità (eventi, operazioni logiche, calcolo combinatorio, assiomi e probabilità elementare, variabili aleatorie discrete e continue). Inferenza statistica (stima puntuale, stima intervallare, test di ipotesi).

Argomenti del programma: The course program is organized in three parts as described below. Descriptive Statistics The data matrix. Types of variables. Frequency tables. Graphical representations. Summary measures of position and dispersion. Association of two quantitative variables, covariance and correlation coefficient. Outline of simple linear regression.