MATH 215 SI

Session 1

Session 1

Lectures 1 - 4

  • 12.1 Three-Dimensional Coordinate Systems
  • 12.2 Vectors
  • 12.3 The Dot Product
  • 12.4 The Cross Product
  • 12.5 Equations of Lines and Planes

12.1 Three-Dimensional Coordinate Systems

  • Defined as \(\mathbb{R}^3 = \{(x,y,z) \mid x,y,z \in \mathbb{R}\}\)
  • We represent any point of space by an ordered triple \((a,b,c)\)

Exercises

12.1 Three-Dimensional Coordinate Systems

  • What does the equation \(x = 4\) represent in \(\mathbb{R}^2\)?
  • What does the same equation represent in \(\mathbb{R}^3\)?
  • Describe and/or sketch the surface in \(\mathbb{R}^3\) represented by the equation \(x+z=2\)

12.2 Vectors

We will define a vector \(\mathbf{v} = \langle v_1, v_2, v_3 \rangle\)

  • Then the magnitude of \(\mathbf{v}\) is given by \(|\mathbf{v}| = \sqrt{v_1^2 + v_2^2 + v_3^2}\)
  • Then the unit vector (direction) of \(\mathbf{v}\) is given by \(\hat{\mathbf{v}} = \mathbf{v} / |\mathbf{v}|\)
  • Vector addition is given by \(\mathbf{v} + \mathbf{u} = \langle v_1 + u_1, v_2 + u_2,..., v_n + u_n \rangle\)
  • Scalar multiplication by \(c\) is given by \(c\mathbf{v} = \langle cv_1, cv_2,..., cv_n\rangle\)
  • The standard basis vectors \(\mathbf{i}\), \(\mathbf{j}\), \(\mathbf{k}\) are unit vectors that point in the direction of the positive \(x\)-, \(y\)-, and \(z\)-axes.
  • Recall the Parallelogram Law

12.2 Vectors

cont.

Properties of Vectors

  • \(\mathbf{a} + \mathbf{b} = \mathbf{b} + \mathbf{a}\)
  • \(\mathbf{a} + \mathbf{0} = \mathbf{a}\)
  • \(c(\mathbf{a} + \mathbf{b}) = c\mathbf{a} + c\mathbf{b}\)
  • \((cd)\mathbf{a} = c(d\mathbf{a})\)
  • \(\mathbf{a} + (\mathbf{b} + \mathbf{c}) = (\mathbf{a} + \mathbf{b}) + \mathbf{c}\)
  • \(\mathbf{a} + (-\mathbf{a}) = \mathbf{0}\)
  • \((c+d)\mathbf{a} = c\mathbf{a} + d\mathbf{a}\)
  • \(1\mathbf{a} = \mathbf{a}\)

Exercises

12.2 Vectors

  • Generate an expression that is equivalent to the vector \(\langle 11, 3, 5 \rangle\) as a linear combination of \(\mathbf{v} = \langle 5, 1, 2 \rangle\) and the standard basis vectors (each vector should appear in your expression).
  • Find a vector that has the same direction as \(\langle 6,2,-3 \rangle\) but has length 4.

12.3 The Dot Product

If \(\mathbf{a} = \langle a_1, a_2, ..., a_n \rangle\) and \(\mathbf{b} = \langle b_1, b_2, ..., b_n \rangle\), then the dot product of \(\mathbf{a}\) and \(\mathbf{b}\) is the number \(\mathbf{a} \cdot \mathbf{b}\) given by \(\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + \cdots + a_n b_n\)

  • The dot product measures how aligned two vectors are
  • If \(\theta\) is the angle between vectors \(\mathbf{a}\) and \(\mathbf{b}\), then \(\mathbf{a} \cdot \mathbf{b} = |\mathbf{a}||\mathbf{b}|\cos{\theta}\)
  • Two vectors \(\mathbf{a}\) and \(\mathbf{b}\) are orthogonal \(\iff \mathbf{a} \cdot \mathbf{b} = 0\)

12.3 The Dot Product

cont.

Properties of the Dot Product

  • \(\mathbf{a} \cdot \mathbf{a} = {|\mathbf{a}|}^2\)
  • \(\mathbf{a} \cdot \mathbf{b} = \mathbf{b} \cdot \mathbf{a}\)
  • \(\mathbf{a} \cdot (\mathbf{b} + \mathbf{c}) = \mathbf{a} \cdot \mathbf{b} + \mathbf{a} \cdot \mathbf{c}\)
  • \((c\mathbf{a}) \cdot \mathbf{b} = c(\mathbf{a} \cdot \mathbf{b}) = \mathbf{a} \cdot (c\mathbf{b})\)
  • \(\mathbf{0} \cdot \mathbf{a} = 0\)

12.3 The Dot Product

cont.

Projections

  • The scalar projection of \(\mathbf{b}\) onto \(\mathbf{a}\) is given by \(\text{comp}_a \mathbf{b} = \frac{\mathbf{a} \cdot \mathbf{b}}{|\mathbf{a}|}\)
  • The vector projection of \(\mathbf{b}\) onto \(\mathbf{a}\) is given by \(\text{proj}_a \mathbf{b} = \left(\frac{\mathbf{a} \cdot \mathbf{b}}{|\mathbf{a}|}\right) \frac{\mathbf{a}}{|\mathbf{a}|}\)

Exercises

12.3 The Dot Product

  • Let \(\mathbf{v} = \langle v_1, v_2, v_3 \rangle\), and let \(\theta_1\) be the angle \(\mathbf{v}\) makes with the \(x\)-axis, \(\theta_2\) be the angle \(\mathbf{v}\) makes with the \(y\)-axis, and \(\theta_3\) be the angle \(\mathbf{v}\) makes with the \(z\)-axis. Evaluate the following expression: \(\cos^2{\theta_1} + \cos^2{\theta_2} + \cos^2{\theta_3}\)

12.4 The Cross Product

If \(\mathbf{a} = \langle a_1, a_2, a_3 \rangle\) and \(\mathbf{b} = \langle b_1, b_2, b_3 \rangle\) then the cross product of \(\mathbf{a}\) and \(\mathbf{b}\) is the vector \(\mathbf{a} \times \mathbf{b}\) given by

\[ \mathbf{a} \times \mathbf{b} = \begin{vmatrix} \mathbf{i} & \mathbf{j} & \mathbf{k} \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \end{vmatrix} \]

  • \(\mathbf{a} \times \mathbf{b}\) is orthogonal to both \(\mathbf{a}\) and \(\mathbf{b}\)
  • \(|\mathbf{a} \times \mathbf{b}| = |\mathbf{a}||\mathbf{b}|\sin{\theta}=\) area of the parallelogram determined by \(\mathbf{a}\) and \(\mathbf{b}\)
  • Two nonzero vectors \(\mathbf{a}\) and \(\mathbf{b}\) are parallel \(\iff \mathbf{a} \times \mathbf{b} = 0\)

12.4 The Cross Product

cont.

Properties of the Cross Product

  • \(\mathbf{a} \times \mathbf{b} = -\mathbf{b} \times \mathbf{a}\)
  • \((c\mathbf{a}) \times \mathbf{b} = c(\mathbf{a} \times \mathbf{b}) = \mathbf{a} \times (c\mathbf{b})\)
  • \(\mathbf{a} \times (\mathbf{b}+\mathbf{c}) = \mathbf{a} \times \mathbf{b} + \mathbf{a} \times \mathbf{c}\)
  • \(\mathbf{a} \cdot (\mathbf{b} \times \mathbf{c}) = (\mathbf{a} \times \mathbf{b}) \cdot \mathbf{c}\)
  • \(\mathbf{a} \times (\mathbf{b} \times \mathbf{c}) = (\mathbf{a} \cdot \mathbf{c})\mathbf{b} - (\mathbf{a} \cdot \mathbf{b})\mathbf{c}\)

Exercises

12.4 The Cross Product

  • Find the cross product \(\mathbf{a} \times \mathbf{b}\) and verify that it is orthogonal to both \(\mathbf{a}\) and \(\mathbf{b}\). Let \(\mathbf{a} = 2\mathbf{j} - 4\mathbf{k}\) and \(\mathbf{b} = -\mathbf{i} +3\mathbf{j} + \mathbf{k}\)

12.5 Equations of Lines and Planes

A line through point \(\mathbf{r}_0\) with direction \(\mathbf{v}\) is given by \(\mathbf{r}(t) = t\mathbf{v} + \mathbf{r}_0\)

  • Note that \(\mathbf{r}\) is a function of \(t\)
  • By eliminating \(t\) we can yield the symmetric equations (not useful in my experience).

A plane through point \(\mathbf{r}_0\) with normal vector \(\mathbf{n}\) is given by \(\mathbf{n} \cdot (\mathbf{r}-\mathbf{r}_0) = 0\)

  • Note that \(\mathbf{r}\) is an arbitrary vector
  • Expanding the expression we yield the scalar equation of the plane given by \(a(x-x_0) + b(y-y_0) + c(z-z_0) = 0\)

12.5 Equations of Lines and Planes

cont.

Distances

  • The distance \(D\) from point \(P_1(x_1,y_1,z_1)\) to the plane \(ax + by + cz + d = 0\) is given by \(D = \frac{|ax_1+by_1+cz_1+d|}{\sqrt{a^2+b^2+c^2}}\)

Exercises

12.5 Equations of Lines and Planes

Suppose \(P_1\) is a plane that contains the points \((0, 3, 0)\), \((-3, 0, 0)\), and \((2, 6, 1)\).

  • Find the equation of the plane \(P_1\)

Let \(P_2\) be the plane that contains the point \((0,2,1)\) and the line \(\mathbf{l}(t) = \langle 2t, t, 1+3t \rangle\)

  • Find the angle between \(P_1\) and \(P_2\)

Fin

This concludes session 1.