Pietro CORETTO | COMPUTATIONAL STATISTICS
Pietro CORETTO COMPUTATIONAL STATISTICS
cod. 0212700130
COMPUTATIONAL STATISTICS
| 0212700130 | |
| DIPARTIMENTO DI SCIENZE AZIENDALI - MANAGEMENT & INNOVATION SYSTEMS | |
| EQF6 | |
| BUSINESS MANAGEMENT | |
| 2020/2021 |
| OBBLIGATORIO | |
| YEAR OF COURSE 3 | |
| YEAR OF DIDACTIC SYSTEM 2014 | |
| PRIMO SEMESTRE |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 5 | 30 | LESSONS |
| Objectives | |
|---|---|
| STUDENTS WILL LEARN HOW TO USE THE R LANGUAGE TO PRODUCE STATISTICAL ANALYSIS AND REPORTS. THEY WILL LEARN THE MOST IMPORTANT COMPUTATIONAL STATISTICAL TOOLS FOR THE ANALYSIS OF BOTH CROSS-SECTION AND TIME SERIES DATA. STUDENTS WILL LEARN HOW TO ESTIMATE AND VALIDATE STATISTICAL MODELS AND PRODUCE DOCUMENTS AND REPORTS AS A SUPPORT FOR DECISION MAKING IN ECONOMIC AND BUSINESS FRAMEWORKS. |
| Prerequisites | |
|---|---|
| INTRODUCTORY STATISTICS |
| Contents | |
|---|---|
| -THE R COMPUTING LANGUAGE -R: DATA STRUCTURES (ARRAYS, DATA.FRAME, LIST) -R: DATA INPUT AND OUTPUT -R: GRAPHIC DEVICE -R: PROGRAMMING AND CONTROL STRUCTUES -R: PROGRAMMING WITH FUNCTIONS AND SCRIPTS -R: THE APPLY FUNCTION FAMILY -ROBUST ESTIMAITON IN LOCATION-SCALE FAMILIES -OUTLIER DETECTION -NUMERICAL AND GRAPHICAL METHODS FOR THE ANALYSIS OF DEPENDENCE -MULTIVARIATE LINEAR REGRESSION MODELS -LOGISTIC REGRESSION -MONTE CARLO SIMULATION METHODS -RESAMPLING METHODS: EMPIRICAL BOOSTRAP AND CROSS-VALIDATION |
| Teaching Methods | |
|---|---|
| THE COURSE CONSISTS OF 30 CLASS HOURS (5 ECTS) WHICH INCLUDE BOTH THEORETICAL METHODS AND CASE STUDIES. |
| Verification of learning | |
|---|---|
| THE FINAL EXAM CONSISTS OF A WRITTEN AND AN ORAL EXAM. BOTH PARTS WILL BE EVALUATED ON A NUMERICAL SCALE BETWEEN 1 AND 30. TO ACCESS THE ORAL PART A MINIMUM OF 18/30 IS REQUIRED FOR THE WRITTEN PART. DURING THE WRITTEN TEST THE STUDENT WILL RECEIVE AN EXAM TRACE AND WILL BE ASKED TO ANSWER 10 QUESTIONS (EACH WITH SCORES RANGING FROM 1 POINT TO 3 POINTS) ON THE ENTIRE PROGRAM OF THE COURSE, USING A DATASET PROVIDED DURING THE EXAM. THE ORAL EXAM (LASTING ABOUT 15 MINUTES) FOCUSES ON THE GENERAL KNOWLEDGE OF THE TOPICS TREATED DURING THE COURSE, THE ABILITY TO PRODUCE A CORRECT STATISTICAL ANALYSIS, THE ABILITY TO CORRECTLY COMMUNICATE THE RESULTS. THE FINAL MARK WILL REFLECT THE EFFECTIVINESS OF THE TOOLS EMPLOYED, OF THE THOROUGHNESS AND LUCIDITY OF ANSWERS. THE FINAL MARK, ON A SCALE BETWEEN 1 AND 30 WITH LAUDE, WILL CONSIDER BOTH THE PERFORMANCE ON THE WRITTEN AND ORAL PART. |
| Texts | |
|---|---|
| LABORATORIO DI STATISTICA CON R 2/ED STEFANO M. IACUS; GUIDO MASAROTTO , MCGRAW HILL WICKHAM, H., E G. GROLEMUND (2016).R FOR DATA SCIENCE: IMPORT, TIDY, TRANSFORM, VI-SUALIZE, AND MODEL DATA. O’REILLY MEDIA ADDITIONAL MATERIALS PROVIDED BY THE INSTRUCTOR DURING THE COURSE |
| More Information | |
|---|---|
| GIVEN THE CHARACTERISTICS OF THE DISCIPLINE, AND ITS THEORETICAL AND PRACTICAL APPROACH, THE ATTENDANCE IS STRONGLY RECOMMENDED, ALTHOUGH NOT MANDATORY. STUDENTS WHO DECIDE NOT TO ATTEND CLASSES ARE ADVISED TO FOLLOW THE SYLLABUS AND THE SCHEDULED TOPICS. |
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