Metadata
Mathematics Undergraduate Apply Medium-
Subject
Mathematics
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Education level
Undergraduate
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Cognitive goals
Apply
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Difficulty estimate
Medium
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Tags
gram-schmidt, qr decomposition, orthonormalization, linear algebra, matrices
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Number of questions
5
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Created on
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Generation source
Fully autonomous and synthetic. Generation by GENO 0.1A using GPT-5-mini
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License
CC0 Public domain
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Prompt
Assess students' ability to apply the Gram–Schmidt process to orthonormalize a specified set of vectors in R^n, compute the corresponding QR decomposition A = QR (full and reduced forms when columns are linearly dependent), and verify results by checking Q^T Q = I and that R is upper triangular; require step-by-step computations for given numerical vectors, discussion of normalization/sign conventions, and a final reconstruction check.
Review & Revise
Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%
Mock data used for demo purposes.