Cira PERNA | STATISTICAL INFERENCE
Cira PERNA STATISTICAL INFERENCE
cod. 0212800009
STATISTICAL INFERENCE
| 0212800009 | |
| DEPARTMENT OF ECONOMICS AND STATISTICS | |
| EQF6 | |
| STATISTICS FOR BIG DATA | |
| 2024/2025 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2018 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 10 | 60 | LESSONS |
| Exam | Date | Session | |
|---|---|---|---|
| PERNA | 11/12/2024 - 09:30 | SESSIONE ORDINARIA | |
| PERNA | 11/12/2024 - 09:30 | SESSIONE DI RECUPERO | |
| PERNA | 07/01/2025 - 09:30 | SESSIONE ORDINARIA | |
| PERNA | 07/01/2025 - 09:30 | SESSIONE DI RECUPERO |
| Objectives | |
|---|---|
| KNOWLEDGE AND UNDERSTANDING THE COURSE AIMS TO GENERALIZE AND DEEPEN SOME KNOWLEDGE ACQUIRED IN PREVIOUS STATISTICS COURSES, IN PARTICULAR SOME TOPICS OF PROBABILITY THEORY WILL BE REVIEWED AND SOME METHODS FOR DERIVING THE SAMPLING DISTRIBUTION OF STATISTICS OF INTEREST WILL BE INTRODUCED. FURTHERMORE, THE FOUNDING PRINCIPLES OF STATISTICAL INFERENCE BASED ON LIKELIHOOD, OF ESTIMATION THEORY AND OF HYPOTHESIS TESTING WILL BE PRESENTED ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING THE STATISTICAL TOOLS INTRODUCED TO THE COURSE WILL BE PRESENTED HIGHLIGHTING SOME RELEVANT THEORETICAL RESULTS AND THE POSSIBLE USE IN EMPIRICAL CONTEXT. THE STUDENT IS GIVEN EVIDENCE OF HOW TO SELECT AND PROPERLY APPLY THE ACQUIRED TOOLS AS WELL AS HOW TO INTERPRET AND COMMENT THE RESULTS OF THE ANALYSIS CARRIED OUT. |
| Prerequisites | |
|---|---|
| ANALISI E VISUALIZZAZIONE DEI DATI STATISTICA SPERIMENTALE E APPLICATA |
| Contents | |
|---|---|
| INTRODUCTION TO PROBABILITY. DISCRETE AND CONTINUOUS RANDOM VARIABLES. PRINCIPLES AND METHODS OF STATISTICAL INFERENCE. RANDOM SAMPLES. SAMPLING DISTRIBUTIONS. ASYMPTOTIC SAMPLING DISTRIBUTIONS. SIMULATION TECHNIQUES FOR THE DETERMINATION OF A SAMPLING DISTRIBUTION. INTRODUCTION TO RESAMPLING METHODS. THE JACKNIFE METHOD. THE BOOTSTAP. EXAMPLES AND APPLICATIONS OF BOOTSTRAP. THE LIKELIHOOD FUNCTION. THEORY OF ESTIMATORS. ESTIMATORS AND ESTIMATES. SUFFICIENCY OF AN ESTIMATOR. FINITE PROPERTIES OF AN ESTIMATOR. ASYMPTOTIC PROPERTIES OF AN ESTIMATOR. GENERAL PRINCIPLES FOR ESTIMATING A PARAMETER. STATISTICAL VALIDITY OF AN ESTIMATOR. METHODS OF BUILDING AN ESTIMATOR. THE METHOD OF MOMENTS AND ITS GENERALIZATIONS. INTRODUCTION TO THE LEAST SQUARES METHOD. MAXIMUM LIKELIHOOD METHOD: PRINCIPLES AND APPLICATIONS. MAXIMUM LIKELIHOOD METHODS: PROPERTIES AND THEOREMS. CONFIDENCE INTERVALS. THE BOOTSTRAP METHOD FOR DETERMINING CONFIDENCE INTERVALS. INTRODUCTION TO HYPOTHESIS TESTING. LOGIC AND CHARACTERISTICS OF THE TEST. PROBABILISTIC STRUCTURE OF THE TEST. LIKELIHOOD RATIO. ASYMPTOTIC STATISTICAL TESTS. TEST ON THE PARAMETERS OF A NORMAL DISTRIBUTION. NONPARAMETRIC TESTS. |
| Teaching Methods | |
|---|---|
| LECTURES |
| Verification of learning | |
|---|---|
| THE EVALUATION OF THE PROFIT IS MADE ON THE BASIS OF A WRITTEN TEST AND AN ORAL TEST. THE WRITTEN TEST TAKES APPROXIMATELY 90 MINUTES AND IS AIMED TO ASSESS THE STUDENT'S ABILITY TO USE THE STATISTICAL TECHNIQUES ACQUIRED DURING THE COURSE. THE TRACK OF THE WRITTEN TEST INCLUDES THREE EXECISES WORTH 1-10 POINTS EACH, FOR A TOTAL SCORE OF 30. THE ORAL TEST, OF ABOUT 20 MINUTES, IS INTENDED 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 | |
|---|---|
| D. PICCOLO, STATISTICA,1998, IL MULINO (III EDIZIONE) |
| More Information | |
|---|---|
| ADDITIONAL MATERIALS WILL BE PROVIDED DURING THE COURSE |
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