LABORATORIO DI STATISTICA E DATA MINING

ECONOMICS LABORATORIO DI STATISTICA E DATA MINING

0222210013
DIPARTIMENTO DI SCIENZE ECONOMICHE E STATISTICHE
EQF7
ECONOMICS
2019/2020



YEAR OF DIDACTIC SYSTEM 2018
PRIMO SEMESTRE
CFUHOURSACTIVITY
1060LESSONS
Objectives
KNOWLEDGE AND UNDERSTANDING:

PROVIDING THE STUDENTS WITH ADVANCED METHODOLOGICAL AND COMPUTATIONAL NONPARAMETRIC TOOLS FOR THE ANALYSIS OF TIME SERIES AND CROSS-SECTION DATASETS.

APPLYING KNOWLEDGE AND UNDERSTANDING:

MAKING STUDENTS ABLE TO IMPLEMENT ADVANCED TECHNIQUES FOR DATA ANALYSIS USING THE R PROGRAMMING LANGUAGE.
Prerequisites
BASIC KNOWLEDGES OF STATISTICS
Contents
INTRODUCTION TO DATA ANALYSIS USING THE STATISTICAL SOFTWARE R: DATA INPUT, DATA CLEANING, MISSING DATA PROCESSING, OUTLIER DETECTION TECHNIQUES, GRAPHS. (12 HOURS)
ELEMENTS OF SIMULATION THEORY. INTRODUCTION TO NONPARAMETRIC METHODS FOR INFERENCE. (6 HOURS)
THE BOOTSTRAP PROCEDURE FOR INFERENCE. BOOTSTRAP FOR DEPENDENT DATA. (18 HOURS)
SMOOTHING FOR DENSITY ESTIMATION AND MAIN PROPERTIES. (12 HOURS)
SMOOTHING FOR REGRESSION AND MAIN PROPERTIES. (12 HOURS)
NOUREAL NETWORK ESTIMATORS. (12 HOURS)
ALL LESSONS INCLUDE EXERCISES AND APPLICATIONS USING R.

Teaching Methods
LECTURES AND COMPUTER LABORATORY SESSIONS
Verification of learning
THE EVALUATION OF THE PROFIT IS MADE ON THE BASIS OF A PRACTICAL TEST AND AN ORAL TEST. THE PRACTICAL TEST IS DEVOTED TO ASSESSING THE STUDENT'S CAPACITY TO APPLY THE TOOLS ACQUIRED DURING THE COURSE TO REALISTIC CONTEXTS. IT CONSISTS IN THE DEVELOPMENT OF A PROJECT WORK, USING THE STATISTICAL SOFTWARE R, IN WHICH A DATASET CHOSEN BY THE INSTRUCTOR IS ANALYSED. THE ORAL TEST, OF ABOUT 15 MINUTES, IS DEVOTED TO EVALUATING THE ARGUMENTATION CAPACITY, THE ACCURACY OF LANGUAGE AND THE ABILITY TO MAKE CRITICAL USE OF THE ACQUIRED STATISTICAL TOOLS. THE FINAL SCORE WILL TAKE INTO ACCOUNT BOTH THE WRITTEN AND ORAL EVALUATIONS.
Texts
- APPLIED SMOOTHING TECHNIQUES FOR DATA ANALYSIS, A. BOWMAN AND A. AZZALINI, CLARENDON PRESS, OXFORD

- ADDITIONAL MATERIALS PROVIDED BY THE TEACHER DURING THE COURSE
More Information
FURTHER MATERIAL (DATA, SOFTWARE, LECTURE NOTES) WILL BE PUBLISHED ON THE INSTRUCTOR'S WEBSITE.
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