3.3 Cramers Rule, Volume, and Linear Transformations McDonald Fall - - PDF document

3 3 cramer s rule volume and linear transformations
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3.3 Cramers Rule, Volume, and Linear Transformations McDonald Fall - - PDF document

NOTE: These slides contain both Sections 3.1 and 3.2. 3.3 Cramers Rule, Volume, and Linear Transformations McDonald Fall 2018, MATH 2210Q, 3.3 Slides 3.3 Homework : Read section and do the reading quiz. Start with practice problems. Hand


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NOTE: These slides contain both Sections 3.1 and 3.2.

3.3 Cramer’s Rule, Volume, and Linear Transformations

McDonald Fall 2018, MATH 2210Q, 3.3 Slides 3.3 Homework: Read section and do the reading quiz. Start with practice problems. ❼ Hand in: TBD. ❼ Recommended: TBD.

3.3.1 Cramer’s rule

Theorem 3.3.1 (Cramer’s Rule). Let A be an invertible n × n matrix. For any b in Rn, the unique solution x of Ax = b has entries given by xi = det Ai(b) det A , i = 1, 2, . . . , n where Ai(b) = [ a1 · · · ai−1 b ai+1 · · · an ] Example 3.3.2. Use Cramer’s rule to solve the system

  • 3x1

− 2x2 = 6 −5x1 + 4x2 = 8 Example 3.3.3. Consider the following system of equations where a = 0. Prove that if a = 24 then the system has exactly one solution. What does the solution set look like?

  • ax

− 6y = −1 4x − y = 3 1

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Definition 3.3.4. The adjugate (or classical adjoint) of A, is adj(A) =       C11 C12 · · · C1n C21 C22 · · · C2n . . . . . . . . . Cn1 Cn2 · · · Cnn      

T

=       C11 C21 · · · Cn1 C12 C22 · · · Cn2 . . . . . . . . . C1n C2n · · · Cnn       . Where Cij = (−1)i+j det Aij. Theorem 3.3.5 (Inverse Formula). Let A be an invertible n × n matrix. Then A−1 = 1 det A adj A. Example 3.3.6. Find the inverse of the matrix A =    2 1 3 1 −1 1 1 4 −2    Remark 3.3.7. This formula for the inverse is really useful for theoretical calculations, but in almost all cases, our algorithm of reducing to the identity is much more efficient. 2

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3.3.2 Determinants as Area or Volume

Theorem 3.3.8. If A is a 2 × 2 matrix, then the area of the parallelogram determined by the columns of A is | det A|. If A is a 3 × 3 matrix, then the volume of the parallelepiped determined by the columns of A is | det A|. Example 3.3.9. Calculate the area of the parallelogram with vertices (0, 0), (1, 2), (2, 3) and (3, 5). Example 3.3.10. Find the area of the parallelogram with vertices (−2, −2), (0, 3), (4, −1) and (6, 4). 3

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Example 3.3.11. Find the area of the parallelepiped with one vertex at the origin, and adjacent vertices (1, 0, −1), (4, 5, 6), (7, 3, 9). Example 3.3.12. Find the area of the triangle with vertices (1, 2), (4, 3), and (3, 5). 4

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3.3.3 Linear Transformations

Theorem 3.3.13. Let T : R2 → R2 be the linear transformation determined by a 2 × 2 matrix A. If S is a parallelogram in R2, then {area of T(S)} = | det A| · {area of S} If T : R3 → R3 is a linear transformation determined by a 3 × 3 matrix A, and S is a parallelepiped in R3, then {volume of T(S)} = | det A| · {volume of S} Let S be the parallelogram determined by the vectors b1 =

  • 1

3

  • and b2 =
  • 2

1

  • , and T : R2 → R2

be a linear transformation with standard matrix A =

  • 1

2 5

  • . Find the area of T(S).

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3.3.4 Additional Notes and Problems

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