Free Online Flashcard Deck

8 Applications of Linear Algebra Free Online FlashCards

Study 8 Applications of Linear Algebra with 12 free online flashcards. Review key terms, definitions, and concepts with this interactive flashcard deck.

12 cards
01
Front

What does a vector represent?

Back

A vector is an ordered list of numbers representing quantities, coordinates, states, or unknowns.

02
Front

What is a matrix used for?

Back

A matrix organizes coefficients or represents a rule that transforms input vectors into output vectors.

03
Front

How is each entry of AxA\mathbf{x} computed?

Back

In a product model, the entry in row ii of AxA\mathbf{x} is the dot product of row ii of AA with x\mathbf{x}.

04
Front

What is the purpose of Gaussian elimination?

Back

Gaussian elimination transforms the augmented matrix [A∣b][A\mid\mathbf{b}] using elementary row operations to reveal pivot and free variables.

05
Front

When does a linear system have infinitely many solutions?

Back

A consistent system has infinitely many solutions when at least one free variable remains.

06
Front

What determinant condition guarantees invertibility?

Back

A square matrix is invertible precisely when det⁡(A)≠0\det(A)\neq 0.

07
Front

What is the determinant formula for a 2×22\times2 matrix?

Back

For A=[abcd]A=\begin{bmatrix}a&b\\c&d\end{bmatrix}, det⁡(A)=ad−bc\det(A)=ad-bc.

08
Front

What geometric information does a determinant provide?

Back

For a two-dimensional transformation, ∣det⁡(A)∣|\det(A)| is the area-scaling factor; a negative determinant also reverses orientation.

09
Front

What conditions define a linear transformation?

Back

A linear transformation preserves vector addition and scalar multiplication: T(u+v)=T(u)+T(v)T(\mathbf{u}+\mathbf{v})=T(\mathbf{u})+T(\mathbf{v}) and T(cu)=cT(u)T(c\mathbf{u})=cT(\mathbf{u}).

10
Front

How is composition of linear transformations represented?

Back

If T1(x)=A1xT_1(\mathbf{x})=A_1\mathbf{x} and T2(x)=A2xT_2(\mathbf{x})=A_2\mathbf{x}, then (T2∘T1)(x)=A2A1x(T_2\circ T_1)(\mathbf{x})=A_2A_1\mathbf{x}.

11
Front

What is the kernel of a linear transformation?

Back

The kernel is the set of inputs mapped to zero: ker⁡(T)={x:T(x)=0}\ker(T)=\{\mathbf{x}:T(\mathbf{x})=\mathbf{0}\}.

12
Front

What is a basis, and what does its size determine?

Back

A basis is a linearly independent spanning set, and the number of vectors in it is the space's dimension.