Inglese

Statistics è un corso introduttivo che non richiede precedenti conoscenze di statistica e che fornisce i concetti e i metodi della statistica descrittiva enfatizzando la comprensione dei principi della raccolta dati, dell’analisi dei dati e delle teorie sottostanti. Un parte significativa del corso è incentrata sull’utilizzo della statistica in casi reali.
I principali argomenti del corso includono:
Introduzione alla statistica
Raccolta dati
Visualizzazione e sintesi dei dati;
Relazioni tra variabili
Comprensione e comparazione delle distribuzioni

Intro Stats, 5th Edition
De Veaux, Velleman & Bock
2018
Pearson

Fornire le competenze per:

1. Elucidare il concetto di variabilità, identificare e porre domande meritevoli di ulteriore investigazione;
2. Pianificare un'indagine su dati statistici che includa l'identificazione di variabili nonchè la proposta di una strategia per la raccolta dei dati, che risponda agli obiettivi dell’indagine.
3. Raccogliere, gestire e archiviare dati statistici pronti per l'analisi.
4. Applicare metodi statistici fondamentali per esplorare, analizzare e visualizzare i dati
5. Interpretare analisi statistiche e trarre conclusioni sul contesto oggetto di studio
6. Utilizzare il pacchetto statistico gratuito R per l'elaborazione statistica e l'analisi dei dati

Conoscenze di base della matematica

Per raggiungere efficacemente gli obiettivi dichiarati, questo corso utilizzerà le seguenti strategie didattiche:
lezioni frontali:

Le lezioni si concentreranno sugli aspetti teorici della statisticha. Sono progettati per sviluppare la comprensione e la conoscenza delle statistiche descrittive e per rafforzare le abilità degli studenti nella raccolta dei dati, nell'analisi dei dati e nelle interpretazioni.
Sessioni di laboratorio
Verranno effettuate esercitazioni in laboratorio per introdurre agli studenti il software R. Lo scopo è quello di sviluppare le capacità analitiche e interpretative dei dati mediante software per l'analisi dei dati statistici

Esame finale basato sulla discussione dei temi previsti dal programma di insegnamento.

PART I: EXPLORING AND UNDERSTANDING DATA
1. Introduction to statistics
1.1 What Is Statistics?
1.2. Data
1.3 Variables
1.4 Models

2. Displaying and Describing Data

2.1 Summarizing and Displaying a Categorical Variable
2.2 Displaying a Quantitative variable
2.3 Shape
2.4 Center
2.5 Spread

3. Relationships Between Categorical Variables — Contingency Tables

3.1 Contingency tables
3.2 Conditional distributions
3.3 Displaying Contingency Tables
3.4 Categorical Variables

4. Understanding and Comparing Distributions

4.1 Displays for Comparing Groups
4.2 Outliers


5. The Standard Deviation as a Ruler and the Normal Model

5.1 Using the standard deviation to Standardize Values
5.2 Shifting and scaling
5.3 Normal models
5.4 Working with Normal Percentiles
5.5 Normal Probability Plots
PART II: EXPLORING RELATIONSHIPS BETWEEN VARIABLES
6. Scatterplots, Association, and Correlation
6.1 Scatterplots
6.2 Correlation
6.3 Warning: Correlation ≠ Causation
6.4 *Straightening Scatterplots
7. Linear Regression

7.1 Least Squares: The Line of “Best Fit”
7.2 The Linear model
7.3 Finding the least squares line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R2–The Variation Accounted for by the Model
7.7 Regression Assumptions and Conditions
8. Regression Wisdom

8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking Variables and Causation
8.5 Working with Summary Values

English

Statistics is an introductory course that assumes no prior knowledge of statistics. Basic statistical concepts and methods are presented in a manner that emphasizes understanding the principles of data collection and analysis as well as those of theory. Much of the course will be devoted to discussions of how statistics is commonly used in the real world.
Main topics include:
Introduction to Statistics
Collecting Data
Displaying and summarizing Data
Relationships Between Variables
Understanding and Comparing Distributions

Intro Stats, 5th Edition
De Veaux, Velleman & Bock
2018
Pearson

To provide the skills to:
1. Elucidate the concept of variation and identify and pose statistical questions requiring investigation
2. Plan a statistical data investigation including identifying variables and measures and proposing a method of data collection that will answer the question posed.
3. Collect, manage and store statistical data ready for analysis.
4. Apply fundamental statistical methods to explore, analyse and visualise data
5. Interpret statistical analysis and draw conclusions in context and in the presence of uncertainty
6. Use the free and powerful statistical package R for statistical computing and reproducible analysis.

Basic Mathematics Skills

To effectively fulfill its stated goals, this course will make use of the following teaching strategies:
Lectures

Lectures will focus on the theoretical aspects of Statistics. They are designed to develop students’ understanding and knowledge of descriptive statistics, and to strengthen students’ skills in data collection, data analysis and interpretations.
Laboratory Sessions
A series of laboratory sessions will be given to familiarise students with the software R. The purpose is to develop students’ data analytical and interpretation skills that are necessary for the analysis of statistical data.

Final examination consisting in the discussion of program themes.

PART I: EXPLORING AND UNDERSTANDING DATA
1. Introduction to statistics
1.1 What Is Statistics?
1.2. Data
1.3 Variables
1.4 Models

2. Displaying and Describing Data

2.1 Summarizing and Displaying a Categorical Variable
2.2 Displaying a Quantitative variable
2.3 Shape
2.4 Center
2.5 Spread

3. Relationships Between Categorical Variables — Contingency Tables

3.1 Contingency tables
3.2 Conditional distributions
3.3 Displaying Contingency Tables
3.4 Categorical Variables

4. Understanding and Comparing Distributions

4.1 Displays for Comparing Groups
4.2 Outliers


5. The Standard Deviation as a Ruler and the Normal Model

5.1 Using the standard deviation to Standardize Values
5.2 Shifting and scaling
5.3 Normal models
5.4 Working with Normal Percentiles
5.5 Normal Probability Plots
PART II: EXPLORING RELATIONSHIPS BETWEEN VARIABLES
6. Scatterplots, Association, and Correlation
6.1 Scatterplots
6.2 Correlation
6.3 Warning: Correlation ≠ Causation
6.4 *Straightening Scatterplots
7. Linear Regression

7.1 Least Squares: The Line of “Best Fit”
7.2 The Linear model
7.3 Finding the least squares line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R2–The Variation Accounted for by the Model
7.7 Regression Assumptions and Conditions
8. Regression Wisdom

8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking Variables and Causation
8.5 Working with Summary Values