DATA CLEANING AND INTEGRATION IN OFFICIAL STATISTICS

Course objectives

Learning goals Knowledge at an intermediate and advanced level of the main issues in official statistics with special attention to data quality Knowledge and understanding Knowledge and understanding of statistical methods within the topics of official statistics in an changing environment Applying knowledge and understanding Ability to apply statistical methods for official statistics problems with emphasis on the data quality process Making judgements Ability of choosing appropriate methods in different problems in official statistics with emphasis on the data quality process Communication skills Ability of communicating results of the analyses in official statistics with emphasis on the data quality process Learning skills Students acquire skills useful to approach more advanced topics in official statistics and data quality management

Channel 1
DONATELLA FIRMANI Lecturers' profile

Program - Frequency - Exams

Course program
Part 1: Statistical Data Editing and Imputation - Systematic Errors - Automatic Editing - Missing Data - Imputation - Selective Editing Part 2: Record Linkage and Statistical Matching - The Fellegi-Sunter approach - Parametric Macro with CIA - Parametric Micro with CIA - Non parametric Macro with CIA - Non parametric Micro with CIA - Parametric Macro without CIA - Non parametric Macro without CIA
Prerequisites
There are no formal requirements. General requirements are foundational understanding of statistics and familiarity with R/Python.
Books
The main material of the course is distributed by the teacher. Useful texts for further reading are: - "Data Quality and Record Linkage Techniques" Thomas N. Herzog, Fritz J. Scheuren and William E. Winkler - "Statistical matching: Theory and practice" D'Orazio, Marcello, Marco Di Zio and Mauro Scanu. Consult the Moodle site of the course for the slides https://elearning.uniroma1.it/course/view.php?id=15153
Frequency
not mandatory
Exam mode
During the oral exam, the candidate is evaluated on their knowledge of the content covered in class. This may involve the ability to answer specific questions, connect concepts, and apply acquired knowledge to practical situations or problems. The ability to respond appropriately, coherently, and accurately to questions is a key element in the overall evaluation.
  • Lesson code10612315
  • Academic year2025/2026
  • CourseStatistical Methods and Applications
  • CurriculumOfficial Statistics (percorso valido anche ai fini del conseguimento del doppio titolo italo-francese)
  • Year1st year
  • Semester2nd semester
  • SSDSECS-S/01
  • CFU6