Database management and processing

ldemo2404  2019-2020  Louvain-la-Neuve

Database management and processing
Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
3 credits
15.0 h + 15.0 h
Q2
Teacher(s)
Schnor Christine;
Language
English
Prerequisites
Preferably, the students should have acquired some basic knowledge on Stata (e.g. through the introductory course to STATA LDEMO2630) and have some knowledge about datasets.
However, no statistical expertise is required since statistical methods are kept to a minimum.
Main themes
Database management and processing provides the foundations needed to gather, handle and analyze complex survey or census data with STATA.
The course focuses on 7 themes:
1.       Introduction to Stata
2.       Variable management (generating and modifying variables, dealing with string variables)
3.       Data cleaning (dealing with missing data, duplicates, and date processing)
4.       Organizing and documenting scripts
5.       Data manipulation in subsets of data and across subgroups
6.       Combining or reshaping datasets
7.       Using loops and other tools to repeat commands over different files or segments of datasets
8. Visualizations and maps
Aims

At the end of this learning unit, the student is able to :

1. be enabled to prepare efficiently survey or census datasets for analysis ;
 
2. handle survey and census data: clean the data, merge and reshape datasets, extract relevant information, apply functions over subset of the data, combine multiple datasets in one project ;
 
3. use data visualizations (plots or maps) as tools to check the data.
 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Teaching methods
All lessons are a mix of a standard lecture and computer-based practical sessions based on real-life examples. The lectures provide the main concepts and tools, as well as basic knowledge required to do the exercises. Assignments are scheduled after each session to apply the procedures on datasets and verify the assimilation of concepts and tools. Corrections are offered at the beginning of each course.
Evaluation methods
The formal assessment takes the form of a written exam based on a specific survey dataset.
Faculty or entity
PSAD


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

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Sociology

Master [120] in Population and Development Studies

Mineure en statistique et science des données

Advanced Master in Quantitative Methods in the Social Sciences