Tidying up Official Statistics with R and GSBPM: Deep Dive into Analysing

Tidying up official statistics with R and GSBPM: Deep Dive into Analysing

Course Leader

Anton Örn Karlsson, Head of Innovation, Statistics Iceland

ESS statisticians working in the production of official statistics, especially data processing and analysis, with some experience in the use of ‘R’. The course should both be relevant for junior as well as senior statisticians.

Sound command of English. Participants should be able to participate in discussions in the course and make short presentations in English for the group. Participants should have knowledge of statistical concepts and methods used in official statistical production and dissemination.

This course is focused on the use of R in analysing data for official statistical production. 

The main objectives of the course are: 

• Present how the Generic Statistical Business Process Model (GSBPM) can be used for organizing the analysis of data for official statistics.

• Show how R can be used in analysing data.

• Introduce how R (and selected libraries) can be used for the different tasks of the analyse process of the GSBPM, e.g. seasonal adjustments, validation of output, variance estimation, and exporting outputs.

The course is designed to be an online full-time self-study course for five days. Students will meet the course leaders over three live sessions:

• Day 1: Monday, 10:00 – 12:00 (GMT). 

  Kick-off meeting: Introduction of teachers and participants via Zoom.

• Day 3: Wednesday, 10:00 – 12:00 (GMT).

  Short presentations from students.

• Day 5: Friday, 12:00 – 13:00 (GMT). 

  Wrap up meeting: Wrap up with students and teachers via Zoom. 

The course platform will be active over five days, from Monday to Friday. During this time, students will watch recorded lectures and work on assignments according to their own schedule. Instructors will be available to students during all active course days via email, chat or short online meetings to answer questions and help them with their code and assignments. Students are also encouraged to seek help from other students and use various web-based sources to complete the assignments.

Lectures will be available on the course platform in advance.

Each learning module will have an assignment where students are given the opportunity to acquire hands-on experience with the use of R in the production of official statistics. The assignments do not require an advanced knowledge of R and mostly deal with using prewritten scripts and answering questions based on them. Students are encouraged to make their own changes to the scripts and try them on their own datasets. Students are required to complete all assignments. Students will not receive a course certificate unless they turn in all assignments.

The course participants will be given an overview of the Generic Statistical Business Process Model and how to apply it to their work in producing official statistics and ensure the quality of the outputs.

At the end of the course the participants will be able to:

• Use R for analysing and validating data for use in the production of official statistics.

• Recognize common R packages and R functions used during the analysing phase in the GSBPM.

• Use tidy methods and techniques to write R syntax.

• Create basic graphs in R using ggplot2.

• Create reusable code and apply best practices in writing and maintaining code.

• Recorded lectures with examples.

• Discussions based on experience from various statistical offices.

• Exercises / Practical applications.

Required Reading 

None.

• https://statswiki.unece.org/display/GSBPM/GSBPM+v5.1 

• https://r4ds.hadley.nz/ 

• https://github.com/SNStatComp/awesome-official-statistics-software 

• https://www.tidyverse.org/ 

• https://r-graph-gallery.com/ggplot2-package.html 

None.

Day 1: Monday December 15th, 

• 10:00 – 12:00 (GMT) Live Session. Kick-off meeting: Introduction of teachers and participants via teams. Also, instructions for short presentation from students due on Wednesday. Form: All students and instructors.
• Students work on assignments.
• Students work on assignments.
• 10:00 – 12:00 (GMT) Live Session.  Short presentations from students.
• Students work on assignments. 
• Students work on assignments
• The last day for students to complete and submit their assignments if they have not already done it. 
• 12:00 – 13:00 (GMT) Live Session. Wrap up meeting: Wrapping up with students and teachers on teams. Form: All students and instructors.

Day 2: Tuesday December 16th,

Day 3: Wednesday December 17^th,

Day 4: Thursday December 18^th,

Day 5: Friday December 19th,