Marcella NIGLIO | DATA ANALYSIS AND REPORTING
Marcella NIGLIO DATA ANALYSIS AND REPORTING
cod. 8861200014
DATA ANALYSIS AND REPORTING
| 8861200014 | |
| DEPARTMENT OF ECONOMICS AND STATISTICS | |
| Corso di Dottorato (D.M.226/2021) | |
| ECONOMICS AND POLICY ANALYSIS OF MARKETS AND FIRMS | |
| 2023/2024 |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2023 | |
| FULL ACADEMIC YEAR |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 4 | 20 | LESSONS |
| Objectives | |
|---|---|
| THE COURSE AIMS TOINTRODUCE STATISTICAL DATA ANALYSIS METHODS AND ELEMENTS OF PROGRAMMING USING SOFTWARE WIDELY USED IN THE SCIENTIFIC COMMUNITY. THE TWO MODULE STRUCTURE ACHIEVES THE FOLLOWING GOAL: TO INTRODUCE A PROGRAMMING LANGUAGE THAT IS THEN USED FOR THE STATISTICAL MULTIDIMENSIONAL DATA ANALYSIS. THIS WILL ALLOW DOCTORAL STUDENTS TO LEARN THE MOST WIDESPREAD MULTIDIMENSIONAL TECHNIQUES BUT ALSO LEARN A PROGRAMMING LANGUAGE THAT CAN BE USED FOR RESEARCH AND WORK PURPOSES. |
| Prerequisites | |
|---|---|
| ATTENDANCE OF THE STATISTICAL COURSES OF THE PREVIOUS TERM. |
| Contents | |
|---|---|
| THE COURSE IS STRUCTURED IN TWO MODULES. THE FIRST MODULE AIMS TO INTRODUCE RSTUDIO AND THE R LANGUAGE: OBJECTS, CYCLES, FUNCTIONS, PACKAGES, DATA IMPORT/EXPORT , EXPLORATIVE DATA ANALYSIS. THE ATTENTION IS THEN FOCUSED ON THE UNIVARIATE AND MULTIVARIATE DATA VISUALIZATION USING THE GGPLOT2 PACKAGE AND ITS MAIN UTILITIES. ALL THESE TOOLS ARE THEN USED TO BUILD A STATISTICAL REPORT. THE STRUCTURE OF A STATISTICAL REPORT IS INTRODUCED, AND THE R-MARKDOWN IS PRESENTED GIVING EMPHASIS ON THE LANGUAGE AND THE MAIN ADVANTAGES THAT IT ALLOWS TO OBTAIN. THE SECOND MODULE PROPOSES AN INTRODUCTION ON THE MAIN MULTIVARIATE STATISTICAL ANALYSIS, ACCORDING TO THE TYPE OF VARIABLES (NUMERIC AND CATEGORICAL) AND TO THE POSSIBLE AIMS OF AN ANALYSIS. IN PARTICULAR, AFTER INTRODUCING THE MAIN INSTRUMENTS FOR AN EXPLANATORY STATISTICAL ANALYSIS (DATA MATRIX, VECTOR OF MEANS, VARIANCE-COVARIANCE MATRIX, CORRELATION MATRIX, AND SO ON), THE MODULE DEALS WITH THE PRINCIPAL COMPONENT ANALYSIS, USED AS A METHOD FOR REDUCING THE NUMBER OF CORRELATED VARIABLES INTO A SMALLER NUMBER OF UNCORRELATED VARIABLES, AND THE CLUSTER ANALYSIS, APPLIED FOR CREATING SOME HOMOGENEOUS GROUPS AMONG THE STATISTICAL UNITS. MOREOVER, THE MODULE ALSO INTRODUCES STATISTICAL CLASSIFICATION. ALL STATISTICAL ANALYSIS ARE EXPLAINED THEORETICALLY AND BY ANALYSING REAL DATASETS WITH THE SOFTWARE R. |
| Teaching Methods | |
|---|---|
| FRONTAL LESSONS |
| Verification of learning | |
|---|---|
| THE EXAM IS THE DISCUSSION OF A PROJECT WORK, IN THE FORM OF PRESENTATION OR SHORT STATISTICAL REPORT. THE PROJECT NEEDS TO CONTAIN METHODOLOGICAL ELEMENTS OF THE STATISTICAL TECHNIQUES USED AND A CASE STUDY WITH DATASETS SELECTED BY THE STUDENT AND PROCESSED BY WRITING A SPECIFIC PROGRAMMING CODE. FOR THE PRESENTATION OF THE PROJECT WORK, EACH PHD STUDENT WILL HAVE 15 MINUTES DURING WHICH THEY WILL PRESENT THEIR WORK TO THE COMMISSION. TO HAVE AT LEAST A "BUONO" RATING, THE DOCTORAL STUDENT HAS TO USE ALL THE DATA ANALYSIS AND REPORTING TECHNIQUES PRESENTED DURING THE LESSONS. THE JUDGMENT MAY BECOME "OTTIMO" IF THE DOCTORAL STUDENT SHOWS THAT HE HAS CONSULTED AND UNDERSTOOD THE RELEVANT LITERATURE AND HAS BEEN ABLE TO APPROPRIATELY APPLY WHAT EXPLAINED IN THE COURSE IN EMPIRICAL CONTEXTS. |
| Texts | |
|---|---|
| BIBLIOGRAPHIC MATERIAL WILL BE RECOMMENDED AT THE BEGINNING OF THE COURSE. |
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