In this program
- Linear systems and elimination
- Matrix operations
- Inverses and determinants
- Least squares and applications
- Eigenvalues for applications
- SVD and PCA (intro)
Least squares and applications
Matrix algebra · STEM / applied
Orthogonal projections onto column spaces (computational)
Objectives
- Orthogonal projections onto column spaces (computational)
- Normal equations
- Least-squares solutions
- Fitting lines and simple models to data
- Markov chains or discrete dynamical systems with matrices (intro)
Study materials
- Study guideComing soon
- Exam StrategyComing soon
- Common MistakesComing soon
- WorksheetsComing soon
- Word problemsComing soon
- Mixed PracticeComing soon
- Multi-Unit ProblemsComing soon
- ReviewComing soon
- Practice testComing soon
- Answer keyComing soon
Interactive practice
Quizzes, typed answers, and flashcards for this unit — coming soon.
- Coming soon
Quiz
Multiple-choice questions with instant feedback
- Coming soon
Typed practice
Type answers and check them
- Coming soon
Flashcards
Vocabulary and key facts
- Coming soon
Mixed quiz
Harder mixed review for this standard