2 vectors

a vector can be expressed as \(\vec{AB}\) or \(\tilde{u}\)

\[\tilde{u}=u_1\tilde{i}+u_2\tilde{j}+u_3\tilde{k}\]

2.1 magnitude and unit vectors

the magnitude of a vector \(|\tilde{u}|\) is the distance of that vector \(\tilde{u}\)

\[|\tilde{u}|=\sqrt{u_1^2+u_2^2+u_3^2}\]

a unit vector \(\hat{u}\) is any vector with magnitude 1

\[\hat{u}=\frac{\tilde{u}}{|\tilde{u}|}\]

2.2 addition and subtraction

\[\tilde{u}+\tilde{v}=(u_1+v_1)\tilde{i}+(u_2+v_2)\tilde{j}+(u_3+v_3)\tilde{k}\]

\[\tilde{u}-\tilde{v}=(u_1-v_1)\tilde{i}+(u_2-v_2)\tilde{j}+(u_3-v_3)\tilde{k}\]

2.3 the zero vector

the zero vector \(\tilde{0}\) has magnitude \(0\) and have no particular direction

\[\tilde{0}=0\tilde{i}+0\tilde{j}+0\tilde{k}\]

note that \(\tilde{u}-\tilde{u}\neq{}0\), but rather \(\tilde{u}-\tilde{u}=\tilde{0}\)

2.4 parallel vectors

two vectors \(\tilde{u}\) and \(\tilde{v}\) are parallel if \(\tilde{u}\) is a scalar multiple of \(\tilde{v}\)

\[\tilde{u}=k\tilde{v},k\in{R}\]

2.5 linear dependence

a set of vectors is linearly dependent if one can be expressed as a linear combination of the others

\[\tilde{u}=p\tilde{v}+q\tilde{w}\]

a set of vectors is linearly independent if its not linearly dependent

2.6 dot product

the dot product always return a real number which is the amount of space covered by the two vector

\[\tilde{u}\cdot{}\tilde{v}=|\tilde{u}||\tilde{v}|\cos(\theta)\] \[\tilde{u}\cdot\tilde{v}=u_1v_1+u_2v_2+u_3v_3\]

  • if \(\tilde{u}\cdot\tilde{v}=|\tilde{u}||\tilde{v}|\) then \(\tilde{u}\) and \(\tilde{v}\) is parallel
  • if \(\tilde{u}\cdot\tilde{v}=0\) and \(\tilde{u},\tilde{v}\neq\tilde{0}\) then \(\tilde{u}\) and \(\tilde{v}\) is perpendicular

2.7 vector resolutes

the scalar resolute of \(\tilde{u}\) in the direction of \(\tilde{v}\) is given by \(\tilde{u}\cdot\hat{v}\) \[\text{or...}\quad\frac{\tilde{u}\cdot\tilde{v}}{|\tilde{v}|}\]

the vector resolute of \(\tilde{u}\) in the direction of \(\tilde{v}\) is given by \((\tilde{u}\cdot\hat{v})\hat{v}\) \[\text{or...}\quad\frac{\tilde{u}\cdot\tilde{v}}{|\tilde{v}|}\tilde{v}\]

2.8 geometric proofs

2.8.1 triangles

  • equilateral triangles have equal length sides and equal angles of \(60^\circ\) at each vertex. it is sufficient to show only one of these properties

  • isosceles triangles have only two sides that are equal in length and two angles that are equal. it is sufficient to show only one of these properties

2.8.2 quadrilaterals

  • squares have equal angles of \(90^\circ\) at each vertex and equal side lengths. a sufficient proof requires showing that both of these properties are true

  • rectangles have equal angles of \(90^\circ\) at each vertex. a sufficient proof requires showing that both pairs of opposite sides are parallet and the there is one \(90^\circ\) angle

  • rhombuses have two pairs of opposite parallel sides, with all sides equal in length. a sufficient proof requires showing that both of these properties are true

  • parallelograms have two pairs of opposite parallel sides. a sufficient proof requires showing that a single pair of opposite sides is parallel and equal in length; the vectors representing two opposite sider are equal

  • trapeziums have one pair of parallel sides. a sufficient proof requires showing that a single pair of opposite sides is parallel