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Linear Algebra Practice Questions: Test Your Knowledge | LearnByTeaching.ai

Challenge your understanding of linear algebra with these 40 multiple-choice questions spanning vector spaces, matrix operations, eigenvalues, and inner product spaces. These questions test both computational skills and the geometric intuition that separates surface-level knowledge from true understanding.

40 questions total

Systems of Equations and Matrix Operations

Test your understanding of systems of equations and matrix operations.

Q1Mediumsystems-of-equations

What is the rank of the matrix [[1, 2, 3], [2, 4, 6], [0, 1, 1]]?

Q2Easysystems-of-equations

A homogeneous system Ax = 0 with 5 unknowns and 3 equations always has:

Q3Mediumsystems-of-equations

If A is a 3x3 matrix with det(A) = 4, what is det(2A)?

Q4Easysystems-of-equations

Which of the following is NOT an elementary row operation?

Q5Mediumsystems-of-equations

If AB = I, which statement is necessarily true?

Q6Mediumsystems-of-equations

The null space of a 4x6 matrix A with rank 3 has dimension:

Q7Mediumsystems-of-equations

What does it mean geometrically when a 2x2 matrix has determinant 0?

Q8Easysystems-of-equations

For the system Ax = b, if A is invertible, the unique solution is:

Q9Mediumsystems-of-equations

The column space of a matrix A is the same as:

Q10Easysystems-of-equations

If A is row equivalent to the identity matrix, then A is:

Vector Spaces and Subspaces

Test your understanding of vector spaces and subspaces.

Q11Mediumvector-spaces

Which of the following is NOT a vector space?

Q12Mediumvector-spaces

The dimension of the vector space of all 3x3 symmetric matrices is:

Q13Mediumvector-spaces

If W is a subspace of R^4 with dim(W) = 2, what is the dimension of its orthogonal complement W^perp?

Q14Mediumvector-spaces

Which of the following sets is a subspace of R^3?

Q15Easyvector-spaces

If vectors v1, v2, v3 in R^3 are linearly independent, they form a:

Q16Mediumvector-spaces

The intersection of two subspaces of a vector space V is:

Q17Hardvector-spaces

A linear transformation T: R^3 -> R^2 can be:

Q18Mediumvector-spaces

What is the dimension of the solution space of a homogeneous system with coefficient matrix of size 5x7 and rank 4?

Q19Hardvector-spaces

The set of all solutions to a non-homogeneous system Ax = b (b ≠ 0) is:

Q20Easyvector-spaces

If {v1, v2, v3, v4} spans R^3, then this set is:

Eigenvalues and Eigenvectors

Test your understanding of eigenvalues and eigenvectors.

Q21Easyeigenvalues-eigenvectors

If A is a 3x3 matrix with eigenvalues 1, 2, and 3, what is det(A)?

Q22Mediumeigenvalues-eigenvectors

If λ is an eigenvalue of A, then λ^2 is an eigenvalue of:

Q23Easyeigenvalues-eigenvectors

A 4x4 matrix with characteristic polynomial (λ-2)^2(λ+1)(λ-3) has eigenvalue 2 with algebraic multiplicity:

Q24Mediumeigenvalues-eigenvectors

A matrix A is diagonalizable if and only if:

Q25Easyeigenvalues-eigenvectors

The eigenvalues of a triangular matrix are:

Q26Mediumeigenvalues-eigenvectors

If A has eigenvalue 0, then A is:

Q27Easyeigenvalues-eigenvectors

The trace of a matrix equals:

Q28Mediumeigenvalues-eigenvectors

If A is a real symmetric matrix, its eigenvalues are:

Q29Easyeigenvalues-eigenvectors

For a 2x2 matrix with eigenvalues 3 and -1, what is the trace?

Q30Mediumeigenvalues-eigenvectors

If A is diagonalizable with A = PDP^(-1), then A^k equals:

Inner Product Spaces and Orthogonality

Test your understanding of inner product spaces and orthogonality.

Q31Easyinner-product-spaces

Two vectors u and v are orthogonal when:

Q32Easyinner-product-spaces

The Gram-Schmidt process takes a set of linearly independent vectors and produces:

Q33Mediuminner-product-spaces

If Q is an orthogonal matrix, then Q^(-1) equals:

Q34Hardinner-product-spaces

The projection of vector b onto the column space of A is given by:

Q35Mediuminner-product-spaces

If {u1, u2, u3} is an orthonormal basis for R^3 and v is any vector in R^3, then v equals:

Q36Mediuminner-product-spaces

The Cauchy-Schwarz inequality states that |u · v| is at most:

Q37Hardinner-product-spaces

In the least squares solution to Ax = b, the residual vector b - Ax* is orthogonal to:

Q38Easyinner-product-spaces

What is the norm of the vector (3, 4)?

Q39Mediuminner-product-spaces

The QR decomposition factors a matrix A into:

Q40Mediuminner-product-spaces

An orthogonal matrix preserves:

Scoring Guide

Total possible: 40

Excellent36-40: Outstanding command of linear algebra. You have strong computational skills and geometric intuition.
Good28-35: Solid understanding with some gaps. Review eigenvalue theory and orthogonal projections.
Needs WorkBelow 28: Revisit the foundations — focus on row reduction, vector space axioms, and the geometric meaning of determinants and eigenvalues.

Study Recommendations

  • Watch 3Blue1Brown's 'Essence of Linear Algebra' series for geometric intuition behind every concept
  • Practice row reduction and eigenvalue computation by hand until the procedures are automatic
  • For every theorem, construct a concrete 2x2 or 3x3 numerical example
  • Connect abstract concepts to applications: PCA for data science, PageRank as an eigenvector problem
  • Use the teach-back method — explain each concept aloud as if teaching a classmate
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