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MATH 235 — Linear Algebra IIMidterm 275 min · 60 marks

CramCore generated

Nov 12, 2025

Actual exam

Nov 15, 2025

Topic overlap6 of 7 topics predicted

Based on internal comparison of topic coverage. Individual results vary by course and materials uploaded.

What the professor handed out

MATH 235 — Linear Algebra II

Midterm 2 · 75 minutes · Total: 60 marks

Q1 [10 marks] — Eigenvalues

Let A be the 3×3 matrix with rows [2, 1, 0], [0, 3, 1], [0, 0, 2].

(a) Find all eigenvalues of A. [4 marks]

(b) For each eigenvalue, find a basis for the eigenspace. [6 marks]

Q2 [10 marks] — Diagonalization

Let B have eigenvalues λ₁ = 1, λ₂ = 4, λ₃ = 4 with corresponding eigenspaces of dimension 1, 2.

(a) Is B diagonalizable? Justify. [4 marks]

(b) If yes, find an invertible P and diagonal D such that B = PDP⁻¹. [6 marks]

Q3 [10 marks] — Orthogonality

Let W = span{v₁, v₂} where v₁ = [1, 1, 0, 1]ᵀ and v₂ = [0, 1, 1, 0]ᵀ.

(a) Apply Gram-Schmidt to {v₁, v₂} to produce an orthonormal basis for W. [6 marks]

(b) Find the orthogonal projection of b = [3, 1, 2, 4]ᵀ onto W. [4 marks]

Q4 [8 marks] — Least Squares

The system Ax = b has no solution. Find the least-squares solution x̂ where:

A = [[1,1],[1,2],[1,3]]   b = [1, 3, 4]ᵀ

Q5 [12 marks] — Symmetric Matrices

Let S be a real symmetric matrix with eigenvalues 2 and 5.

(a) Prove that the eigenspaces of S are orthogonal. [6 marks]

(b) Find an orthogonal matrix Q and diagonal D such that S = QDQᵀ. [6 marks]

Q6 [10 marks] — Complex Eigenvalues

The matrix C = [[0, −2], [2, 0]] has complex eigenvalues.

(a) Find the eigenvalues and eigenvectors of C. [6 marks]

(b) Describe the geometric effect of C on ℝ². [4 marks]

What CramCore generated 3 days earlier

MATH 235 — Linear Algebra II

Practice Midterm 2 · 75 minutes · Total: 60 marks

Q1 [10 marks] — Eigenvalues & Eigenvectors

Consider the matrix M = [[3, 1, 0], [0, 3, 0], [0, 0, 5]].

(a) Find all eigenvalues of M and their algebraic multiplicities. [4 marks]

(b) Determine a basis for each eigenspace. Is M diagonalizable? [6 marks]

Q2 [10 marks] — Diagonalization

Suppose A is a 3×3 matrix with characteristic polynomial p(λ) = −(λ − 2)²(λ − 7).

(a) Under what conditions on the eigenspaces is A diagonalizable? [4 marks]

(b) Given that A is diagonalizable, compute A⁴. [6 marks]

Q3 [10 marks] — Orthogonal Projections

Let W be the subspace of ℝ⁴ spanned by u₁ = [1, 0, 1, 1]ᵀ and u₂ = [1, 1, 0, −1]ᵀ.

(a) Verify that {u₁, u₂} is orthogonal. [2 marks]

(b) Find projᵣ y for y = [2, 3, 1, 0]ᵀ. [4 marks]

(c) Find the distance from y to W. [4 marks]

Q4 [8 marks] — Least Squares Regression

Fit a line y = c₀ + c₁t to the data points (0, 1), (1, 2), (2, 4) using least squares.

Set up and solve the normal equations AᵀAx̂ = Aᵀb.

Q5 [12 marks] — Spectral Theorem

Let S = [[5, 2], [2, 2]] be a real symmetric matrix.

(a) Find the eigenvalues of S. [4 marks]

(b) Find an orthonormal eigenbasis and write the orthogonal diagonalization S = QDQᵀ. [8 marks]

Q6 [10 marks] — Change of Basis

Let B = {[1,1]ᵀ, [1,−1]ᵀ} and B' = {[2,1]ᵀ, [1,1]ᵀ} be two bases for ℝ².

(a) Find the change-of-basis matrix from B to B'. [6 marks]

(b) If [v]ᵣ = [3, −1]ᵀ, find [v]ᵣ'. [4 marks]

Topic-by-topic breakdown

Green = CramCore predicted this topic. Grey = appeared on only one exam.

Eigenvalues & eigenvectorsMatch
Diagonalization (conditions + computation)Match
Gram-Schmidt / Orthogonal projectionsMatch
Least squaresMatch
Symmetric matrices / Spectral theoremMatch
Complex eigenvalues (actual exam only)Unique
Change of basis (CramCore only)Unique
Matrix powers via diagonalizationMatch

How does CramCore predict this?

CramCore reads your syllabus, notes, and past assessments. It figures out where your course is in the term, what format your professor uses, and which topics are due. Then it builds a practice exam that mirrors the real thing — without ever seeing it.