Giuseppina ALBANO | STATISTICS
Giuseppina ALBANO STATISTICS
cod. 1212500010
STATISTICS
| 1212500010 | |
| DEPARTMENT OF MANAGEMENT & INNOVATION SYSTEMS | |
| EQF6 | |
| DIPLOMATIC, INTERNATIONAL AND GLOBAL SECURITY STUDIES | |
| 2024/2025 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2019 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 9 | 63 | LESSONS |
| Exam | Date | Session | |
|---|---|---|---|
| ALBANO | 12/12/2024 - 09:30 | SESSIONE ORDINARIA | |
| ALBANO | 12/12/2024 - 09:30 | SESSIONE DI RECUPERO | |
| ALBANO | 09/01/2025 - 09:30 | SESSIONE ORDINARIA | |
| ALBANO | 09/01/2025 - 09:30 | SESSIONE DI RECUPERO |
| 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 AND INTERNATIONAL MANAGEMENT. MAKING JUDGMENTS: THE METHODS COVERED IN THIS COURSE ARE WIDELY APPLIED TO THE STUDY OF SOCIO-MICROECONOMIC PROBLEMS. STUDENTS WILL BE REQUIRED TO APPLY METHODS TO REAL DATA AND COMMUNICATE ON THE INTERPRETATION OF THE RESULTS. 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 | |
|---|---|
| BASIC MATHEMATICAL KNOWLEDGE IS REQUIRED |
| Contents | |
|---|---|
| INTRODUCTORY CONCEPTS (6 H) WHAT IS STATISTICS. STATISTICAL SURVEY. TYPES OF INFORMATION AND MEASUREMENT SCALES. CENSUSES AND SAMPLING. SAMPLING ERRORS AND POTENTIAL SOURCES OF DISTORTION. ORGANIZE THE DATA IN THE TABLE. DESCRIPTIVE STATISTICS (10 H) ABSOLUTE AND RELATIVE FREQUENCY DISTRIBUTIONS. GRAPHIC REPRESENTATIONS: BAR DIAGRAMS, PIE CHARTS, HISTOGRAMS, GRAPHICS FOR TIME SERIES. POSITION AND ITS MEASUREMENT: ARITHMETIC AVERAGE, WEIGHTED ARITHMETIC AVERAGE, MEDIAN AND FASHION. VARIABILITY AND ITS MEASUREMENT: RANGE, VARIANCE, STANDARD DEVIATION. TRANSFORMATION OF DATA. Z-SCORES. POSITION AND VARIABILITY INDICES FOR GROUPED DATA. THE PROBLEM OF THE OUTLIERS. STRONG POSITION INDICES: MEDIAN, QUARTILES AND OTHER PERCENTILES. ROBUST VARIABILITY INDICES. FIVE SUMMARY AND BOXPLOT. PARALLEL BOXPLOTS. RELATIONS BETWEEN VARIABLES. CORRELATION COEFFICIENT. THE SIMPLE LINEAR REGRESSION MODEL (6 H) SIMPLE LINEAR REGRESSION. INTERPRETATION OF PARAMETERS. VALIDATION OF THE MODEL. GOODNESS OF COMBINATION. THEORY OF PROBABILITIES (13 H) INTRODUCTION. COMBINATORY CALCULATION. PROBABILITY DISTRIBUTIONS FOR DISCRETE VARIABLES. EXPECTED VALUE AND VARIANCE OF A DISCRETE RANDOM VARIABLE. MAIN MODELS OF DISCRETE RANDOM VARIABLES: UNIFORM, BERNOULLI, BINOMIAL. CONTINUOUS RANDOM VARIABLES. THE NORMAL RANDOM VARIABLE. THE STANDARDIZED NORMAL RANDOM VARIABLE. STUDENT AND CHI-SQUARE RANDOM VARIABLES T. TRANSFORMATIONS OF NORMAL RANDOM VARIABLES. THE CENTRAL LIMIT THEOREM. INFERENCE: POINT ESTIMATION (10 H) THE INFERENTIAL LOGIC. PARAMETERS AND STATISTICS. THE SAMPLE DISTRIBUTION. EFFECT OF THE SAMPLE SIZE ON THE SAMPLE DISTRIBUTION. ESTIMATORS OF THE MEAN, OF THE VARIANCE AND OF THE PROPORTION. INFERENCE: INTERVAL ESTIMATION (6 H) CONFIDENCE INTERVALS. LEVEL OF CONFIDENCE. CONFIDENCE INTERVALS FOR THE AVERAGE AND FOR THE PROPORTION. INFERENCE: HYPOTHESIS TEST (6 H) THE LOGIC OF THE HYPOTHESIS TEST. VERIFICATION OF HYPOTHESIS ON THE MEAN AND PROPORTION. THE LINK BETWEEN THE VERIFICATION OF HYPOTHESIS AND CONFIDENCE INTERVALS. INFERENCE: NON PARAMETRIC TESTS (6 H) THE CHI-SQUARE TEST. GOODNESS OF FIT AND INDEPENDENCE BETWEEN VARIABLES. USE OF EXCEL TO ILLUSTRATE SOME CASE STUDIES |
| Teaching Methods | |
|---|---|
| THE COURSE CONSISTS OF 63 HOURS OF LECTURES. EACH LESSON IS STRUCTURED IN A THEORETICAL PART AND A PART OF APPLICATIONS IN CASE STUDIES. |
| Verification of learning | |
|---|---|
| THE EVALUATION IS BASED ON A WRITTEN AND AN ORAL EXAMINATION. THE WRITTEN EXAM CONSISTS OF 3 NUMERICAL EXERCISES, EACH OF ONES HAS A MAXIMUM SCORE OF 10 POINTS. THE EXAM IS PASSED WHEN THE STUDENT ACHIEVES AT LEAST 18. THE ORAL EXAMINATION IS A DISCUSSION ABOUT THE TOPICS OF THE WRITTEN EXAMINATION AND OF THE THEORETICAL PART. |
| Texts | |
|---|---|
| M. SULLIVAN III. FONDAMENTI DI STATISTICA. PEARSON. STATISTICA - L'ARTE E LA SCIENZA D'IMPARARE DAI DATI. AUTORI: ALAN AGRESTI - CHRISTINE FRANKLIN, 2016, PEARSON ED.(O EDIZIONI SUCCESSIVE) ALTERNATIVE: STATISTICA, LEVINE DAVID M.; KREHBIEL TIMOTHY C.; BERENSON MARK L. 2011, 5 ED.(O SUCCESSIVE), EDITOREPEARSON (COLLANA STATISTICA) D. FREEDMAN, R. PISANI, R. PURVES - STATISTICS - W. W. NORTON & COMPANY (2007, 6TH EDITION) |
| More Information | |
|---|---|
| FURTHER MATERIALS WILL BE AVAILABLE ON THE COURSE WEBPAGE. |
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