20684 - STATA PREPARATORY COURSE

To feel comfortable in this course, students should be familiar with basic statistical concepts (i.e. frequency distribution, average, standard deviation, probability, bivariate descriptive statistics …) as taught in a first level statistical course. Basic computer knowledge is given as acquired (i.e. file manager use, basic knowledge of Excel ...).

Stata is a statistical software package widely adopted in a scholar and research environment. The aim of this preparatory course is to help students begin their university studies in a Master of Science with comfort and competence, since in many courses basic Stata topics will be taken for granted. The course is designed for students who have little or no experience with Stata application and intend to develop the knowledge of this useful and user-friendly software for business and economics data analysis. The course, that wants to be an introduction to the statistical software package, has three main objectives: - to present Stata's structure and how it works; - to demonstrate the potentialities of the software for analyzing data, using real data; - to enable students to do, by their own, basic statistical analyses.

• Stata IDE overview
• Variables management
• Data file management
• Preparing data for analysis
• Exploratory data analysis
• Graphic representations
• Hypothesis testing
• Linear regression and its diagnostics (OLS only)
• Introduction to using time series data
• Coding with Stata

• Use different types of dataset
• Clean and prepare data for subsequent analysis (pre-processing phase)
• Produce basic descriptive analyses by means of simple statistical tables, measures and graphs
• Estimate a linear regression model (OLS only)
• Work with time series
• Read and edit Stata scripts

• Understand which kind of data are needed by a specific algorithm and how to adapt data accordingly
• Perform and read simple exploratory data analyses
• Interpret the main outputs of regression

• Face-to-face lectures
• Exercises (exercises, database, software etc.)
• Interactive class activities (role playing, business game, simulation, online forum, instant polls)

• The face-to-face lectures are held in IT classrooms, so that each student has their own PC to use Stata together with the teacher
• Every lesson combines the presentation of syllabus topics followed by examples and in class exercises
• After each lesson, students will be able to download exercises from the course web page on Bboard. These exercises are meant as self-assessment of the learning aspects indicated, by comparing students' own solutions with the ones provided on Bboard (mostly Stata scripts)
• For doubts or clarifications, students can use the dedicated online forum on the elearning page of the course or send an email to the teacher. However, all the answers will always be published in the forum
• To collect classroom feedback from both in presence and in distance students, the teacher might use instant polls during the lessons

In order to measure the acquisition of the learning outcomes mentioned above, the self-assessment will be based on practical exercises, carried out both in class and independently at home.

• Slides, starting dataset and final scripts will be shared with students at the beginning of the lesson (download from Bboard)
• After each lesson, homeworks with solutions will be available on Bboard
• Additional on line materials will be indicated during the course
• Suggested optional bibliography (with different degrees of detail relating to the Statistics topic):

  • Felix Bittmann, Stata: A Really Short Introduction, De Gruyter Oldenbourg, 2019

  • Lisa Daniels, Nicholas W. Minot, An Introduction to Statistics and Data Analysis Using Stata: From Research Design to Final Report, SAGE Publications, 2019

  • L.C. Hamilton, Statistics with STATA: Version 12, 8th Edition, Cengage, 2012