20684 - STATA PREPARATORY COURSE
IT Education Center
Course taught in English
Course Director:
MARIA CHIARA DEBERNARDI
MARIA CHIARA DEBERNARDI
Suggested background knowledge
To feel comfortable in this course, students should be familiar with basic statistical concepts (i.e., frequency distribution, average, standard deviation, basic probability, bivariate descriptive statistics…) as taught in an introductory statistics course.
Familiarity with basic computer skills and Excel (or other spreadsheet software) is expected.
Mission & Content Summary
MISSION
Stata is a powerful statistical software package essential in academic and research domains. This preparatory course aims to equip students with foundational skills in Stata, addressing the software's fundamental requirements often presumed in their MS coursework. Designed for students with minimal or no prior Stata experience, the course provides a comprehensive introduction to data analysis with Stata in business and economics contexts.
Key objectives:
- introduce Stata's architectural framework and operational mechanics;
- demonstrate data analysis capabilities through real-world datasets;
- develop students' independent statistical analysis competencies;
- establish best practices in research project data management and code organization.
CONTENT SUMMARY
- Stata IDE overview
- Intro to coding with Stata
- Variables management
- Data file management
- Preparing data for analysis
- Exploratory data analysis
- Graphic representations
- Hypothesis testing
- Linear regression and its diagnostics (OLS only)
- Management of research projects (data files, do-files, documentation)
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
- Navigate and manipulate diverse dataset formats
- Execute comprehensive data cleaning and apply preprocessing techniques
- Generate descriptive statistical analyses using tables, summary measures, and graphical representations
- Construct and interpret Ordinary Least Squares (OLS) linear regression models
- Develop proficiency in reading, writing, and editing Stata scripts
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
- Select and transform datasets to meet specific analytical model requirements
- Conduct systematic exploratory data analysis
- Critically interpret regression model outputs
- Design and structure research project documentation and materials
Teaching methods
- Lectures
DETAILS
-
Online prerecorded video lectures accessible through Bboard, the eLearning platform
-
Students are invited to reach out to the lecturer if they need help understanding the course content or have specific questions
Assessment methods
| Continuous assessment | Partial exams | General exam | |
|---|---|---|---|
|
x |
ATTENDING AND NOT ATTENDING STUDENTS
This optional preparatory course does not include a final formal assessment.
Learning outcomes will be evaluated through self-paced online assessments, designed to validate students' independent mastery of the course content.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
- Comprehensive course materials (lecture slides, initial datasets, and annotated scripts) will be accessible via Bocconi's Bboard platform
- Supplementary online resources will be recommended throughout the course
For in-depth exploration, students are encouraged to consult the optional bibliography:
Introductory level
- Bittmann, F. (2019). Stata: A Really Short Introduction. De Gruyter Oldenbourg.
Intermediate level
- Daniels, L., Minot, N. W. (2025). An Introduction to Statistics and Data Analysis Using Stata: From Research Design to Final Report (2nd ed.). SAGE Publications.
Advanced level
- Hamilton, L. C. (2013). Statistics with STATA: Version 12 (8th ed.). Cengage Learning.
Last change 28/05/2025 17:14