ldemo2630  2021-2022  Louvain-la-Neuve

3 credits
15.0 h
Q1
Teacher(s)
Language
French
Content
The course is structured around 11 themes:
  • Installing Stata and getting started with the software: windows, do-file, browser
  • Data types in Stata and data import in various formats
  • Variable format and labels
  • Variable creation and recoding
  • Using basic commands
  • Data manipulation
  • Creating graphs
  • Merging and appending data files
  • Descriptive analysis: measures of central tendency and dispersion
  • Basic statistical inference: Chi-square and t-tests.
Teaching methods
The course is given in the form of inverted classes. Introductory videos, course notes and exercises are available on Moodle. The face-to-face sessions will be limited to questions and answers about any difficulties encountered. Students are expected to view the videos and perform the manipulations presented in the videos, answer a quizz, and complete exercises prior to the sessions. A detailed curriculum is available on Moodle.
Evaluation methods
January session
An interim evaluation is organized towards the end of October, on Moodle and Stata. It is rated on 5 points. 
The final evaluation, in January, consists of two parts:
- An assignment consisting in data analyis with the Stata software (10 points). The data and topic are made available one week before the date of delivery of the work. 
- An exam in the computer room, on Stata and Moodle (5 points), consisting of questions about Stata manipulations and general knowledge of the software. In the event of a change in health conditions, this exam could be organized remotely.
September session
Same type of exam as in January.
Online resources
Bibliography
  • Acock, Alan C. (2018), A Gentle Introduction to Stata (6th Edition), Stata Press, College Station.
Teaching materials
  • Acock, Alan C. (2018), A Gentle Introduction to Stata (6th Edition), Stata Press, College Station.
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Population and Development Studies

Advanced Master in Quantitative Methods in the Social Sciences