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Massimo Aria

Viviamo nel "big data age", qualunque attività umana, qualsiasi azione, produce dati.Questo corso affronta le diverse fasi dell’indagine statistica, dal campionamento statistico all’utilizzo degli strumenti inferenziali per ottenere stime, puntuali o intervallari, e per verificare la plausibilità di ipotesi su una o più caratteristiche della popolazione oggetto di studio.In altre parole, lo scopo formativo del corso è di condurre lo studente verso una matura capacità di sintesi e di astrazione nella formalizzazione e nell’analisi dei problemi economico-gestionali attraverso l’impiego degli strumenti di statistica inferenziale ritenuti più adeguati agli obiettivi di analisi e alle caratteristiche dei dati raccolti.

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Viviamo nel "big data age", qualunque attività umana, qualsiasi azione, produce dati.Questo corso affronta le diverse fasi dell’indagine statistica, dal campionamento statistico all’utilizzo degli strumenti inferenziali per ottenere stime, puntuali o intervallari, e per verificare la plausibilità di ipotesi su una o più caratteristiche della popolazione oggetto di studio.In altre parole, lo scopo formativo del corso è di condurre lo studente verso una matura capacità di sintesi e di astrazione nella formalizzazione e nell’analisi dei problemi economico-gestionali attraverso l’impiego degli strumenti di statistica inferenziale ritenuti più adeguati agli obiettivi di analisi e alle caratteristiche dei dati raccolti.

Today, we live in a big data age where all human activities and actions produce data. In this course, we will trace the steps of statistical surveys: from statistical sampling, to the inferential tools used for interval and point estimates and for verifying the plausibility of hypotheses on one or more characteristics of the population studied. In other words, the scope of this course is to provide the students with a sensible synthetic ability as well as with a mature competence of abstraction when formalizing and analyzing the economic and managerial problems with the most appropriate tools.

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What's inside

Learning objectives

  • • analizzare ed elaborare i dati e le loro caratteristiche• acquisire capacità di risoluzione economico - gestionale • principi di base per lavorare con i big data.
  • In this course you will learn how to:• analyze and process data and their characteristics;• develop your skills to solve economic and managerial problems;• master the basic concepts of big data.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Consente di sviluppare competenze nell'analisi e nell'elaborazione dei dati, essenziali per i professionisti del settore economico-gestionale
Fornisce un'introduzione ai principi di base del Big Data, un argomento di crescente importanza nel mondo aziendale
Il corso è progettato per sviluppare capacità di risoluzione dei problemi specifici del settore economico-gestionale, rendendolo particolarmente prezioso per gli studenti interessati a queste aree
È tenuto dal Prof. Massimo Aria, noto accademico ed esperto nel campo della statistica inferenziale, che garantisce l'affidabilità e l'accuratezza del materiale del corso
Il corso è ben strutturato e fornisce una sequenza logica di argomenti, rendendolo facile da seguire e comprendere anche per i principianti

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Analisi dei dati with these activities:
Collect and review all the materials
Organizing your notes, assignments, and quizzes, will help you begin to learn how to best manage and study the material
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  • Gather all your notes, assignments, and quizzes
  • Review each item carefully
  • Take notes on any key concepts or ideas
  • Organize your materials in a way that makes sense to you
  • Review your materials regularly
Comprehend probability concepts
Review probability concepts to build a strong foundation for Statistical Inference.
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  • Revisit probability axioms, definitions, and theorems
  • Practice solving probability problems involving counting techniques
  • Review conditional probability and Bayes' theorem
Review statistical concepts
Review key statistical concepts to strengthen your understanding and prepare for the course
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  • Go over your notes from previous statistics courses
  • Read introductory chapters of the course textbook
  • Complete practice problems or online quizzes
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Watch tutorials on statistical concepts
Watching tutorials can help you learn new concepts and techniques, and reinforce what you've already learned
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  • Find a tutorial on a topic you're interested in
  • Watch the tutorial
  • Take notes on any key concepts or ideas
  • Try to apply what you've learned to a practice exercise
Esercitazioni di campionamento
Eseguire esercitazioni di campionamento aiuterà gli studenti a rafforzare la loro comprensione dei principi del campionamento statistico e a sviluppare le loro capacità di campionamento pratico.
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  • Rivedi i concetti di base del campionamento statistico
  • Scegli una popolazione e una tecnica di campionamento appropriata
  • Raccogli i dati e analizza i risultati
Follow online tutorials on statistical sampling
Enhance your understanding of statistical sampling methods through interactive tutorials
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  • Identify reputable online resources for statistical tutorials
  • Select tutorials that cover the types of sampling relevant to the course
  • Follow the tutorials step-by-step and complete any practice exercises
Practice data analysis exercises
Repetition of key concepts and techniques through practice will help improve your overall understanding of the material and build confidence
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  • Find a practice exercise
  • Solve the practice exercise
  • Check your answers
  • Review the material if you make a mistake
Join a study group to discuss course topics
Engage in peer discussions and exchange insights to enhance your learning
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  • Find or form a study group with classmates
  • Establish regular meeting times and topics
  • Take turns presenting concepts or leading discussions
  • Actively participate in discussions and ask questions
Solve practice problems on statistical inference
Reinforce your understanding of statistical inference by practicing with real-world data sets
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  • Find online platforms or textbooks with practice problems
  • Choose problems that cover different types of statistical inference
  • Work through the problems step-by-step
  • Verify your answers using provided solutions
Partecipa a un gruppo di studio con i tuoi compagni di corso
Collabora con i tuoi compagni per migliorare la comprensione del materiale del corso attraverso discussioni e quiz reciproci.
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  • Forma un gruppo di studio con 2-3 compagni di corso.
  • Stabilisci un programma di incontri regolari.
  • Discutete gli argomenti del corso, ponetevi domande a vicenda e completate i quiz insieme.
Presentazione su un'applicazione Big Data
La creazione di una presentazione su un'applicazione Big Data aiuterà gli studenti a comprendere meglio il potenziale e le sfide dell'utilizzo di Big Data nel mondo reale.
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  • Scegli un'applicazione Big Data di interesse
  • Ricerca l'applicazione e le sue implicazioni
  • Crea una presentazione che descriva l'applicazione, i suoi vantaggi e le sue sfide
Exercises on Hypothesis Testing
Enhance understanding of hypothesis testing through regular practice drills.
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  • Solve problems on formulating hypotheses
  • Practice conducting significance tests
  • Interpret the results of hypothesis tests
Create a visual representation of statistical concepts
Solidify your grasp of statistical concepts by creating visual representations
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  • Choose a statistical concept to focus on
  • Research different data visualization techniques
  • Create your visual representation using appropriate software or tools
  • Present or share your visualization with others
Analyze real-world data
Gain hands-on experience in analyzing real-world data using statistical inference techniques.
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  • Acquire and clean the data
  • Exploratory data analysis and feature engineering
  • Apply statistical models and machine learning algorithms
  • Evaluate and interpret the results
Fai volontariato in un'organizzazione che utilizza tecniche statistiche
Metti in pratica le tue abilità statistiche e fai la differenza nella tua comunità facendo volontariato.
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  • Identifica le organizzazioni nella tua zona che utilizzano tecniche statistiche.
  • Contatta l'organizzazione e chiedi informazioni sulle opportunità di volontariato.
  • Partecipa regolarmente alle attività di volontariato e contribuisci con le tue competenze statistiche.
Develop a statistical model
Apply statistical inference concepts to create a statistical model for real-world data analysis.
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  • Identify the problem and gather data
  • Choose appropriate statistical methods and build the model
  • Validate and interpret the model
  • Communicate the results effectively

Career center

Learners who complete Analisi dei dati will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts use data to develop and implement investment strategies. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make investment recommendations.
Data Scientist
Data Scientists use their knowledge of math, statistics, and computer science to extract insights from data. This course will help you build a foundation in statistical analysis, which is essential for success in this role. You will also learn about working with big data, which is increasingly important in this field.
Statistician
Statisticians collect, analyze, interpret, and present data. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to draw conclusions, and present your findings in a clear and concise way.
Risk Analyst
Risk Analysts use data to identify and assess risks. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make recommendations for managing risk.
Operations Research Analyst
Operations Research Analysts use data to solve problems and improve efficiency in organizations. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make recommendations for improvement.
Data Engineer
Data Engineers build and maintain the systems that store and process data. This course can help you develop the skills needed to succeed in this role, teaching you how to work with big data, use statistical tools to build models, and design and implement data pipelines.
Actuary
Actuaries use data to assess risk and make financial decisions. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make recommendations for managing risk.
Financial Analyst
Financial Analysts use data to make investment recommendations and advise clients on financial matters. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze financial data, use statistical tools to make predictions, and present your findings in a clear and concise way.
Consultant
Consultants use data to help organizations solve problems and improve performance. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to make recommendations, and develop custom reporting tools of your own.
Insurance Analyst
Insurance Analysts use data to assess risk and make insurance decisions. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make recommendations for managing risk. Particularly valuable is your study of big data, as big data is an essential skill for understanding modern insurance risk.
Data Analyst
Data Analysts study the large amounts of data in order to draw conclusions and provide solutions for various types of business issues. This course provides foundational knowledge that is useful for any Data Analyst, as it teaches students the basic principles of working with big data, and how to solve economic and managerial problems using data.
Auditor
Auditors use data to assess financial risks and ensure compliance with laws and regulations. This course can help you develop the skills needed to succeed in this role, teaching you how to analyze data, use statistical tools to build models, and make recommendations for improving internal controls.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and trends. This course can help you develop the skills needed to succeed in this role, teaching you how to design and conduct surveys, analyze data, and present your findings.
Business Analyst
Business Analysts help organizations improve their performance by developing and implementing data-driven solutions. The skills and knowledge learned in this course, particularly in the area of big data analysis, would be highly valuable to someone in this role.
Software Engineer
Software Engineers build and maintain software applications. This course may be useful for Software Engineers who want to specialize in data analysis or big data. You will learn the basics of statistical analysis, how to work with big data, and how to use statistical tools to build models.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Analisi dei dati.
Provides a comprehensive overview of machine learning. It would be a valuable resource for students who want to learn more about this topic.
Questo libro fornisce una panoramica completa dell'analisi dei dati con R. Sarebbe una risorsa preziosa per gli studenti che vogliono saperne di più su questo argomento.
Provides a gentle introduction to the R programming language and the basics of statistics. It would be a useful reference for students who are new to either of these topics.
Provides a broad overview of big data and its implications for society. It would be helpful for students who want to understand the potential and challenges of big data.

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