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Directions: You may work to solve these problems in groups, but all written work must be your own. Show all work; no credit for solutions without work..

  1. [1.8.{13-16}] Use a rectangular coordinate system to plot 𝐮 = [ 5 2 ], 𝐯 = [ − 2 4 ] and their images under the given transformation T. (Make a separate sketch for each.) Describe geometrically what T does to each vector in ℝ2.

    1. T(𝐱) = [ − 1 0 0 − 1 ] [ x1 x2 ]
    2. T(𝐱) = [ 0.5 0 0 0.5 ] [ x1 x2 ]
    3. T(𝐱) = [ 0 0 0 1 ] [ x1 x2 ]
    4. T(𝐱) = [ 0 1 1 0 ] [ x1 x2 ]
  2. [1.8.17] Let T : ℝ2 → ℝ2 be a linear transformation that maps 𝐮 = [ 5 2 ] to [ 2 1 ] and maps 𝐯 = [ 1 3 ] to [ − 1 3 ]. Use the fact that T is linear to find the images under T of 3𝐮, 2𝐯, and 3𝐮 + 2𝐯.
  3. [1.8.32] Suppose vectors 𝐯1,…,𝐯p span ℝn, and let T : ℝn → ℝn be a linear transformation. Suppose T(𝐯𝐢) = 0 for 1 ≤i ≤p. Show that T is the zero transformation (i.e. T(𝐱) = 0 for each 𝐱 ∈ ℝn).
  4. [1.8.{40,41}] Show that the following transformations are not linear.

    1. [ x1 x2 ] ↦ [ 4x1 − 2x2 3|x2| ].
    2. [ x1 x2 ] ↦ [ 2x1 − 3x2 x1 + 4 5x2 ].
  5. [1.9] True/False. Justify your answer.

    1. A linear transformation T : ℝn → ℝm is completely determined by its effect on the columns of the n ×n identity matrix.
    2. If T : ℝ2 → ℝ2 rotates vectors about the origin through an angle ϕ, then T is a linear transformation.
    3. The columns of the standard matrix for a linear transformation from ℝn to ℝm are the images of the columns of the n ×n identity matrix.
    4. When two linear transformations are performed one after another, the combined effect may not always be a linear transformation.
    5. Not every linear transformation from ℝn to ℝm is a matrix transformation.