SIAP e-Learning Courses

Welcome to your e-Learning portal for official statistics

e-Learning courses
11 - 22 June 2018 | Online
e-Learning Course R for Official Statistics
This e-Learning course introduces participants to the basic operations of the R and its application to official statistics. R is an open source is statistical analysis package which is rapidly gaining users in all fields of statistics. The focus of the course in on the use of R for common tasks within as official statisticians’ work, rather than on statistical theory and methods.
9 May - 5 June 2018 | Online
e-Learning Course on Introduction of Official Statistics
This e-Learning course introduces participants to the principles, systems and processes involved in the production of official statistics, both nation-ally and internationally. The focus of the course in on the big ideas that underpin official statisticians’ work, rather than on statistical theory and methods.
21 May - 14 June 2018 | On-line
e-Learning course on Food balance sheet

This is an e-learning course, will cover topics on Food Balance Sheet (FBS), relating to
 Basic concepts and main uses related to FBS
 Process for compiling FBS, in particular, how to collect the necessary information, fill the supply and utilization account, standardize and aggregate the estimates and apply various balancing and imputation of missing data methods
 Compile FBS and derive per capita estimates using the recommended and alternative approaches


Objective: Improve the capacity of countries to adopt cost-effective and reliable methods for producing minimum set of agricultural and rural statistics
11 - 22 June 2018 | Online
e-Learning Course onR for Official Statistics

This e-Learning course introduces participants to the basic operations of the R and its application to official statistics. R is an open source is statistical analysis package which is rapidly gaining users in all fields of statistics. The focus of the course in on the use of R for common tasks within as official statisticians’ work, rather than on statistical theory and methods. Students will be able to install R and perform basic tasks such as importing data, deriving new variables, and calculating aggregates using survey weights by the end of the course.