Analytical learning pathway
This analytical pathway matches relevant analytical training to the specialist competencies within the Government Statistician Group (GSG) competency framework.
It is split by the different job grades within the GSG profession.
Please note:
- These are suggestions for training.
- Successfully undertaking a training course is not sufficient by itself to demonstrate competency achievement.
- The examples may not be relevant for all – training requirements should be considered against the needs of the individual and their role.
- All training should be discussed with line managers first.
- It may be that individuals require training at a higher or lower grade than the one indicated below. For example, you do not need to be a Principal Statistician to take the MSc in Data Analytics for Government, it is available to all grades.
GSG competency framework: level 1 (pdf, 0.1MB)
Acquiring data
Courses:
- Quality Assurance of Administrative Data (QAAD) workshop
- Awareness in administrative data
- Awareness in geography for statistics
- Introduction to sample design and estimation in business surveys
- Introduction to sample design and estimation in social surveys
- Awareness in questionnaire design
- Introduction to statistical disclosure control
- Big data and data science explained
- Awareness in data ethics
Data analysis
Courses:
- Quality statistics in government
- Awareness in small area estimation
- Awareness in data linkage
- Awareness in geography for statistics
- Introduction to sample design and estimation in business surveys
- Introduction to sample design and estimation in social surveys
- Introduction to statistical disclosure control
- Awareness in editing and imputation
- Introduction to index numbers
- Awareness in seasonal adjustment
- Introduction to National Accounts
- Awareness in forecasting
- Awareness in time series
- Awareness of new coding tools
- Introduction to R
- Introduction to Python
- Introduction to Pyspark
- Foundations of SQL
- Intermediate data science with R
- Best practice in programming – clean code
- Introduction to unit testing
- Introduction to Git
- Introduction to machine learning
- Modules of the MSc in Data Analytics for Government
Presenting data
Courses:
- Quality in government statistics
- Writing about quality, uncertainty and change
- Working with users
- Introduction to data visualisation
- Modules of the MSc in Data Analytics for Government
GSG competency framework: level 2 (pdf, 0.13MB)
Acquiring data
Courses:
- Introduction to administrative data
- Introduction to geography for statistics
- Introduction to data linking
- Introduction to questionnaire design and testing
- Introduction to sample design and estimation in social surveys
- Introduction to sample design and estimation in business surveys
- Big data and data science explained
- Awareness in data ethics
Data analysis
Courses:
- Quality in government statistics
- Introduction to geography for statistics
- Introduction to data linkage
- Introduction to sample design and estimation in social surveys
- Introduction to sample design and estimation in business surveys
- Introduction to statistical disclosure control
- Introduction to R
- Introduction to Python
- Awareness of new coding tools
- Introduction to editing and imputation
- Introduction to index numbers
- Introduction to seasonal adjustment
- Introduction to National Accounts
- Introduction to Pyspark
- Foundations of SQL
- Intermediate data science with R
- Best practice in programming – clean code
- Introduction to unit testing
- Introduction to Git
- Fundamental Theories in Machine Learning
- Introduction to machine learning
- Advanced Natural Language Processing in Python
- Modules of the MSc in Data Analytics for Government
Presenting data
Courses:
- Quality in government statistics
- Introduction to statistical disclosure control
- Writing about quality, uncertainty and change
- Working with users
- Presenting confidently
- Report writing
- Introduction to data visualisation
GSG competency framework: level 2 (pdf, 0.13MB)
Acquiring data
Courses:
- Intermediate geography for statistics and spatial analysis
- Introduction to questionnaire design and testing
- Intermediate sample design and estimation for social surveys
- Intermediate sample design and estimation for business surveys
- Big data and data science explained
Data analysis
Courses:
- Intermediate geography for statistics and spatial analysis
- Intermediate sample design and estimation for social surveys
- Intermediate sample design and estimation for business surveys
- Introduction to small area estimation
- Quality in government statistics
- Intermediate editing and imputation
- Intermediate index numbers
- Awareness of new coding tools
- Introduction to R
- Introduction to Python
- Introduction to Pyspark
- Foundations of SQL
- Intermediate data science with R
- Best practice in programming – clean code
- Introduction to unit testing
- Introduction to Git
- Fundamental Theories in Machine Learning
- Introduction to machine learning
- Advanced Natural Language Processing in Python
- Modules of the MSc in Data Analytics for Government
Presenting data
Courses:
- Writing about quality, uncertainty and change
- Working with users
- Advising, briefing and drafting
- Introduction to data visualisation
- Modules of the MSc in Data Analytics for Government
GSG competency framework: level 3 (pdf, 0.13MB)
Acquiring data
Courses:
- Intermediate geography for statistics and spatial analysis
- Intermediate sample design and estimation for social surveys
- Intermediate sample design and estimation for business surveys
- Introduction to small area estimation
- Big data and data science explained
Data analysis
Courses:
- Intermediate geography for statistics and spatial analysis
- Intermediate sample design and estimation for social surveys
- Intermediate sample design and estimation for business surveys
- Introduction to small area estimation
- Intermediate data science with R
- Intermediate editing and imputation
- Intermediate index numbers
- Awareness of new coding tools
- Introduction to R
- Introduction to Python
- Introduction to Pyspark
- Foundations of SQL
- Intermediate data science with R
- Best practice in programming – clean code
- Introduction to unit testing
- Introduction to Git
- Fundamental Theories in Machine Learning
- Introduction to machine learning
- Advanced Natural Language Processing in Python
- Art of the possible – data science in government
- Modules of the MSc in Data Analytics for Government
Presenting data
Courses:
- Writing about quality, uncertainty and change
- Working with users
- Introduction to data visualisation
- Presenting confidently
- Advising, briefing and drafting
- Collaboration across departments, government and beyond
- Modules of the MSc in Data Analytics for Government
GSG competency framework: level 3 (pdf, 0.13MB)
Acquiring data
Courses:
Data analysis
Courses:
- Art of the possible – data science in government
- Modules from the MSc in Data Analytics for Government
- Awareness of new coding tools
- Quality in government statistics
Presenting data
Courses:
- Writing about quality, uncertainty and change
- Working with users
- Introduction to data visualisation
- Embracing digital to lead and innovate