Math Visualization List
Determinant
2x2 & 3x3 Determinants
Cramer's Rule
Permutations & Inversions
Permutation Definition & Expansion
Properties of Determinants: Row Operations
Minors & Cofactors
Two-Row Laplace Expansion
Vandermonde Determinant
Matrix Operations
Matrix Addition, Subtraction & Scalar Multiplication
Matrix Multiplication & Power
Transpose, Determinant & Adjoint
Inverse Matrix & Matrix Equations
Elementary Transformations, Echelon & Canonical Form
Probability & Statistics
Conditional Probability, Independence & Total Probability
Discrete Probability Distributions
PMF & CDF
2D Random Vectors
Conditional Probability Distributions
Bayes' Theorem
Numerical Characteristics of Random Variables
Higher Moments & Covariance Matrix
Law of Iterated Expectations
Independence, Mean Independence & Uncorrelated
Continuous Statistical Distributions
Vector Operations
Vector Addition, Subtraction & Scalar Multiplication
Linear Combination, Span & Basis
Matrices as Transformations
Composition of Transformations
3D Linear Transformations
Determinant
Inverse, Column Space & Rank
Cross-Dimensional Transformations
Vector Angle
Cross Product
Change of Basis
Eigenvectors & Eigenvalues
Function Vector Spaces
Geometric Interpretation of Cramer's Rule
Gravity Simulation
Eigenvectors & Eigenvalues
Directions that "stretch only, don't rotate" under transformation.
Move your mouse to find directions where the gray input vector aligns with the orange output vector.
Transformation Matrix A
2.0
1.0
0.0
1.0
Current Status:
Searching for eigen direction...
Typical Presets:
Geometric motivation for diagonalization:
If we can find enough eigenvectors as a new basis, in this new coordinate system, matrix A becomes a "diagonal matrix" with values only on the diagonal. The transformation decomposes into simple axis-aligned stretches.