Data Science · Data in Context
Virginia SOL DS.1
Virginia SOL DS.1 is part of the Data in Context strand in Data Science (Math). Under this Standards of Learning objective, students identify problems suitable for data-driven solutions and define the stages of the data science cycle. Below is what DS.1 covers in plain language, the specific skills it is assessed on, the key concepts to review, and how to practice DS.1 for the Virginia SOL test.
What SOL DS.1 means
Identify problems suitable for data-driven solutions and define the stages of the data science cycle.
Skills you’ll practice for DS.1
- Identify characteristics of problems that benefit from a data-driven approach.
- Formulate questions based on contextual information.
- Determine relevant data types for a given problem context.
- Define relationships between variables and constants in a problem.
- Create a measurable hypothesis for a data science problem.
- Define the stages of the data science cycle and their interconnections.
- Identify constraints of a data-driven approach to problem-solving.
Key concepts covered by DS.1
- data-driven problem solving
- problem identification
- data suitability
- question formulation
- contextual analysis
- hypothesis generation
- data relevance
- contextual data
- data types
- variable relationships
- constant relationships
- data relationships
- measurable hypothesis
- data hypothesis
- hypothesis formulation
- data cycle stages
- data science process
- data workflow
- data constraints
- limitations of data science
- problem constraints
How to study and practice SOL DS.1
Start with a quick diagnostic to see whether DS.1 is already solid, then work each skill above with guided notes, flashcards, and SOL-style practice questions. For official released items, see our Virginia SOL practice tests guide and how to study for the SOL test.
Related Data Science standards in Data in Context
- DS.2 — Design a data project plan aligned with the data science cycle, including sampling methodology.
Frequently asked questions about SOL DS.1
What is Virginia SOL DS.1?
SOL DS.1 is a Data Science Standard of Learning in the Data in Context strand. It expects students to identify problems suitable for data-driven solutions and define the stages of the data science cycle.
What skills does SOL DS.1 cover?
SOL DS.1 is assessed on 7 skills: identify characteristics of problems that benefit from a data-driven approach; formulate questions based on contextual information; determine relevant data types for a given problem context; define relationships between variables and constants in a problem; create a measurable hypothesis for a data science problem; define the stages of the data science cycle and their interconnections; identify constraints of a data-driven approach to problem-solving.
What strand of Data Science is SOL DS.1 in?
SOL DS.1 belongs to the Data in Context reporting strand of the Data Science Virginia Standards of Learning.
How do I study and practice for SOL DS.1?
Start with a diagnostic to see whether DS.1 is already solid, then work the 7 skills above with guided notes, flashcards, and SOL-style practice questions. For official released items, see the Virginia SOL practice tests guide.