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Course 2019-2020 a.y.

20684 - STATA PREPARATORY COURSE

All Programs
IT Education Center

Course taught in English

Go to class group/s: 1

DSBA (I sem. - P) - PPA (I sem. - P)
Course Director:
MARIA CHIARA DEBERNARDI

Classes: 1 (I sem.)
Instructors:
Class 1: 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, 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 ...).


Mission & Content Summary
MISSION

Stata is a general-purpose statistical software package widely adopted in a scholar and research environment. The aim of the preparatory course in Stata is to help students begin their university studies in a Master of Science with comfort and competence. In many courses, basic Stata topics are taken for granted. The course is designed for students who have little or no experience with Stata and intend to develop the knowledge of this useful and user-friendly software for business and economics data analysis. The course has three main objectives: - to present the structure and philosophy of Stata. - to demonstrate the potentialities of the software for analyzing data with real examples. - to make students able to do, by their own, statistical analysis at basic and intermediate levels.

CONTENT SUMMARY
  • Stata IDE overview.
  • Variables management.
  • Data file management.
  • Preparing data for analysis.
  • Exploratory data analysis.
  • Graphic representations.
  • Hypothesis testing.
  • Linear regression and its diagnostics.
  • Working with time series data.
  • Programming with Stata.

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Use data files got from different sources.
  • Clean and prepare data for subsequent analysis.
  • Produce basic descriptive analyses by means of simple statistical tables, measures and graphs.
  • Estimate a linear regression model.
  • Work with time series.
  • Read and edit Stata scripts.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Understand which kind of data are needed by a specific algorithm and how to adapt data accordingly.
  • Perform and read simple exploratory data analysis.
  • Interpret the main outputs of regression.

Teaching methods
  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)
DETAILS

The face-to-face lectures are held in IT classrooms, so that each student has a PC available to use Stata simultaneously with the teacher.

  • Every lesson combines the presentation of syllabus topics followed by examples and in class exercises.
  • After each lesson, students are able to download exercises from the course web page on Bboard. These exercises are used as self-assessment of the learning aspects indicated, by comparing students' own solutions with the ones provided on Bboard (mostly Stata scripts).

Assessment methods
  Continuous assessment Partial exams General exam
  • Self-evaluation
  • x    
    ATTENDING AND NOT ATTENDING STUDENTS

    With the purpose of measuring the acquisition of the above-mentioned learning outcomes, the self-assessment will be based on practical exercises and closed-ended questions (i.e. a series of "multiple choice" questions).


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS
    • The slides are shared with students at the beginning of the lesson, and will be uploaded on Bboard later.
    • Additional on line materials are indicated during the course.
    • Suggested optional bibliography: L.C. HAMILTON, Statistics with STATA: Version 12, 8th Edition, Cengage, 2012.
    Last change 24/06/2019 18:06