Data Science · Data Modeling
Virginia SOL DS.11
Virginia SOL DS.11 is part of the Data Modeling strand in Data Science (Math). Under this Standards of Learning objective, students select statistical models and tests to extract actionable knowledge from data. Below is what DS.11 covers in plain language, the specific skills it is assessed on, the key concepts to review, and how to practice DS.11 for the Virginia SOL test.
What SOL DS.11 means
Select statistical models and tests to extract actionable knowledge from data.
Skills you’ll practice for DS.11
- Calculate theoretical probability of random events and compare to observed frequencies.
- Describe the normal curve based on mean and standard deviation of a univariate dataset.
- Fit nonlinear models to datasets and use them to predict unobserved data values.
- Select pairs of variables that identify meaningful clusters of data.
- Select an appropriate statistical distribution and test its goodness of fit based on context.
Key concepts covered by DS.11
- theoretical probability
- observed frequencies
- probability calculation
- normal curve
- mean
- standard deviation
- univariate data
- nonlinear models
- data fitting
- prediction
- unobserved data
- variable clustering
- data clusters
- cluster identification
- statistical distribution
- goodness of fit
- distribution selection
- contextual testing
How to study and practice SOL DS.11
Start with a quick diagnostic to see whether DS.11 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 Modeling
- DS.7 — Assess the reliability of source data for mathematical modeling.
- DS.8 — Acquire and prepare big datasets for modeling and analysis.
- DS.9 — Select and analyze data models to make predictions while assessing accuracy and uncertainty.
- DS.10 — Summarize and interpret data in conventional and emerging visualizations.
Frequently asked questions about SOL DS.11
What is Virginia SOL DS.11?
SOL DS.11 is a Data Science Standard of Learning in the Data Modeling strand. It expects students to select statistical models and tests to extract actionable knowledge from data.
What skills does SOL DS.11 cover?
SOL DS.11 is assessed on 5 skills: calculate theoretical probability of random events and compare to observed frequencies; describe the normal curve based on mean and standard deviation of a univariate dataset; fit nonlinear models to datasets and use them to predict unobserved data values; select pairs of variables that identify meaningful clusters of data; select an appropriate statistical distribution and test its goodness of fit based on context.
What strand of Data Science is SOL DS.11 in?
SOL DS.11 belongs to the Data Modeling reporting strand of the Data Science Virginia Standards of Learning.
How do I study and practice for SOL DS.11?
Start with a diagnostic to see whether DS.11 is already solid, then work the 5 skills above with guided notes, flashcards, and SOL-style practice questions. For official released items, see the Virginia SOL practice tests guide.