Marcella NIGLIO | Statistics
Marcella NIGLIO Statistics
cod. 0212400007
STATISTICS
| 0212400007 | |
| DEPARTMENT OF ECONOMICS AND STATISTICS | |
| EQF6 | |
| ECONOMICS | |
| 2022/2023 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2016 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 10 | 60 | LESSONS |
| Objectives | |
|---|---|
| KNOWLEDGE AND UNDERSTANDING - ACQUIRE THE MAIN TOOLS OF DESCRIPTIVE STATISTICS AND STATISTICAL INFERENCE - ACQUIRE MAIN TOOLS FOR BUSINESS ORIENTED DECISION MAKING - ACQUIRE KNOWLEDGE OF STATISTICAL MODELING WITH APPLICATIONS TO REAL DATASETS APPLYING KNOWLEDGE AND UNDERSTANDING STUDENTS WILL BE EXPOSED TO CASE STUDIES TO UNDERSTAND THE ADVANTAGES GAINED FROM APPLYING STATISTICAL ANALYSIS TO QUANTITATIVE PROBLEMS ARISING FROM BUSINESS MANAGEMENT. MAKING JUDGEMENTS THE METHODOLOGIES COVERED IN THIS COURSE ARE WIDELY APPLIED TO THE STUDY OF FIRM-LEVEL MICROECONOMIC PROBLEMS. COMMUNICATION SKILLS THE CLASSES WILL FOCUS ON THE PRESENTATION OF THE RESULTS OBTAINED APPLYING STATISTICAL METHODOLOGIES ON REAL DATASETS. THE EMPHASIS WILL BE PUT ON THE USE OF GRAPHICAL TOOLS AND SUMMARY STATISTICS AS RELEVANT INFORMATION DEVICE SUPPORTING THE DECISION MAKING PROCESS. LEARNING SKILLS THE LECTURE WILL AIM TO STIMULATE THE STUDENT'S QUANTITATIVE INTELLECTUAL ABILITIES. STUDENTS WILL BE ASKED TO DEVELOP THOSE SKILLS NEEDED TO STUDY FURTHER QUANTITATIVE PROBLEMS WITH A HIGH LEVEL OF AUTONOMY. |
| Prerequisites | |
|---|---|
| REQUIREMENTS: MATHEMATICS |
| Contents | |
|---|---|
| MODULE I, DATA ANALYSIS: STATISTICAL SURVEY, FREQUENCY DISTRIBUTIONS FOR UNIVARIATE DATA, LOCATION MEASURES, SCALE MEASURES, SHAPE MEASURES (SYMMETRY AND KURTOSIS), DISTRIBUTIONS FOR BIVARIATE DATA. MODULE II, PROBABILITY: INTRODUCTION TO ELEMENTARY PROBABILITY THEORY, RANDOM VARIABLES (CONTINUOUS AND DISCRETE), BASIC PROBABILITY MODELS, ELEMENTARY INTRODUCTION TO LIMIT THEOREMS FOR SEQUENCE OF RANDOM VARIABLES. MODULE III. INFERENCE: PARAMETRIC ESTIMATION, INTRODUCTION TO ESTIMATION THEORY, POINT ESTIMATION, HYPOTHESIS TESTING, CONFIDENCE INTERVALS, LINEAR MODELS (ESTIMATION AND TESTING) |
| Teaching Methods | |
|---|---|
| ALL LECTURES (60 HOURES) WILL BE HELD IN CLASSROMM. DURING THE COURSE THEORETICAL TOPICS ARE BALANCED WITH TEIR PRACTICAL ISSUES. AT LEAST FOUR LECTURES WILL BE DEVOTED TO CASE STUDIES. |
| Verification of learning | |
|---|---|
| THE FINAL EXAM IS CHARACTERIZED BY TWO PARTS: THE WRITTEN AND THE ORAL EXAMINATION. THE FIRST PART (1H AND 30 MIN) INCLUDES EXERCISES ON THE THREE MODULES OF THE COURSE WHEREAS THE ORAL PART (ABOUT 20 MIN) IS BASED ON AN INTERVIEW. THE ORAL INTERVIEW CAN BE TAKEN IF THE STUDENT HAS PASSED THE WRITTEN EXAM WITH A MINIMUM SCORE OF 18. THE FINAL SCORE IS THE MEAN OF THE SCORES OBTAINED AT THE FIRST AND SECOND PART OF THE EXAM. |
| Texts | |
|---|---|
| CASELLA G. AND BERGER R.L., STATISTICAL INFERENCE, DUXBURY ADVANCED SERIES. |
| More Information | |
|---|---|
| FOR MORE INFORMATION: DOCENTI.UNISA.IT/MARCELLA.NIGLIO |
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