Cira PERNA | STATISTICAL INFERENCE
Cira PERNA STATISTICAL INFERENCE
cod. 0212800009
STATISTICAL INFERENCE
| 0212800009 | |
| DIPARTIMENTO DI SCIENZE ECONOMICHE E STATISTICHE | |
| EQF6 | |
| STATISTICA PER I BIG DATA | |
| 2019/2020 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2018 | |
| PRIMO SEMESTRE |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 10 | 60 | LESSONS |
| Objectives | |
|---|---|
KNOWLEDGE AND ABILITY OF COMPREHENSION THE COURSE AIMS AT EXAMINING AND GENERALIZING SOME IMPORTANT TOPICS WHICH HAVE BEEN DEALT IN PREVIOUS STATISTICS COURSES-IN PARTICULAR SOME ISSUES OF PROBABILITY THEORY WILL BE REVIEWED AND TECHNIQUES FOR FINDING THE DISTRIBUTION OF A STATISTIC OF INTEREST BASIC PRINCIPLES OF STATISTICAL INFERENCE BASED ON THE LIKELIHOOD WILL ALSO BE COVERED ALONG WITH THE THEORY OF ESTIMATION AND OF THE HYPOTHESIS TESTING ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING STATISTICAL TOOLS INTRODUCED IN THE COURSE WILL BE PRESENTED WITH THE PURPOSE TO HIGHLIGHT SOME IMPORTANT THEORETICAL RESULTS AND THEIR POSSIBLE IMPLEMENTATION IN EMPIRICAL CONTEXTS THE STUDENT WILL BE GIVEN EVIDENCE OF HOW TO SELECT AND USE THE APPROPRIATE STATISTICAL TOOLS AS WELL AS HOW TO INTERPRET AND COMMENT THE RESULTS OF THE ANALYZES PERFORMED |
| 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. |
| Teaching Methods | |
|---|---|
| LECTURES |
| Verification of learning | |
|---|---|
| THE METHOD OF VERIFICATION OF LEARNING CONSISTS OF A WRITTEN TEST AIMED TO ASSESS THE ABILITY TO USE THE STATISTICAL TECHNIQUES ACQUIRED AND AN ORAL EXAM TO TEST THEIR METHODOLOGICAL IMPLICATIONS. |
| Texts | |
|---|---|
| D. PICCOLO, STATISTICA,1998, IL MULINO (III EDIZIONE) |
| More Information | |
|---|---|
| ADDITIONAL MATERIALS WILL BE PROVIDED DURING THE COURSE |
BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2021-02-19]
