Applied maths, statistics and scientific practices

Applied mathematics and statistics involves applying analytical methods including exploratory data analysis, visualisation and statistical testing to help make accurate recommendations.

Imenukuliwa kutoka UK GDaD PCF.

Viwango

1. Uelewa: You can:

show an understanding of the benefits of applied mathematics and statistics, and can use this knowledge to carry out data science tasks
carry out general analysis techniques for data inspection, exploration and visualisation
interpret statistical output effectively and accurately
show an awareness of different performance and accuracy metrics for statistical assessment and validation
2. Utendaji: You can:

apply analytical methods including exploratory data analysis and statistical testing to a specific data set, to reach accurate and reliable conclusions
understand and use different performance and accuracy metrics for model validation in data science projects, hypothesis testing and information retrieval
compare selected applied mathematics and statistical methods and identify their differences
access and use the statistical and scientific tools available within the organisation
3. Mtaalamu: You can:

apply designated quantitative techniques such as time series analysis, optimisation and simulation to create and embed appropriate models for analysis and prediction
provide guidance on matching data sources with relevant applied mathematics and statistical techniques to meet analysis goals
apply appropriate statistical techniques to available data to discover new relations and offer insight into research problems, helping to improve organisational processes and support decision making
access and use the statistical tools available within the organisation
4. Bingwa: You can:

identify opportunities to develop statistical insight, reports and models to support organisational objectives, while collaborating across the organisation effectively
critique statistical analyses
use a variety of data analytics techniques (such as data mining and prescriptive and predictive analytics) for complex data analysis through the whole data life cycle
use model outputs to produce evidence and help design services and policies
understand a broad range of statistical tools, particularly those deployed within the organisation, and can use these appropriately and help others to use them

Contains public sector information from the UK Government Digital and Data Profession Capability Framework (https://understand-digital-data-roles-skills.service.gov.uk/), licensed under the Open Government Licence v3.0. © Crown copyright.

Ujuzi wa karibu zaidi wa ESCO

apply statistical analysis techniques (ulinganifu wa karibu)
statistics (ulinganifu wa karibu)
apply scientific methods (ulinganifu mwembamba)

Contains ESCO v1.2.1 data (https://esco.ec.europa.eu/). © European Union. Reuse authorised under Commission Decision 2011/833/EU.

Ngazi za majukumu zinazotarajia ujuzi huu

Ngazi ya jukumu	Jukumu	Daraja	Kiwango kinachotarajiwa
Mhandisi mwandamizi wa kujifunza kwa mashine	Mhandisi wa kujifunza kwa mashine	7	Mtaalamu
Mhandisi kiongozi wa kujifunza kwa mashine	Mhandisi wa kujifunza kwa mashine	8b	Mtaalamu
Mwanasayansi wa data mwanafunzi	Mwanasayansi wa data	4	Uelewa
Mwanasayansi msaidizi wa data	Mwanasayansi wa data	5	Utendaji
Mwanasayansi wa data	Mwanasayansi wa data	6	Mtaalamu
Mwanasayansi mkuu wa data	Mwanasayansi wa data	7	Bingwa
Mwanasayansi kiongozi wa data	Mwanasayansi wa data	8a	Bingwa
Mkuu wa sayansi ya data	Mwanasayansi wa data	8b	Bingwa