Part 1: Vector Basics ➡️ Introduction to Vectors
Part 1 of 7
What Is a Vector?
A vector is a quantity with both magnitude (length) and direction .
Examples: velocity, force, displacement. Compare with scalars (magnitude only): speed, mass, temperature.
Notation
Arrow notation: v ⃗ \vec{v} v , A B ⃗ \vec{AB} A B (from A A A to B B B )
Component form: v ⃗ = ⟨ a , b ⟩ \vec{v} = \langle a, b \rangle v = ⟨ a , b ⟩ or v ⃗ = a i + b j \vec{v} = a\mathbf{i} + b\mathbf{j} v = a i + b j
i = ⟨ 1 , 0 ⟩ \mathbf{i} = \langle 1, 0 \rangle i = ⟨ 1 , 0 ⟩ (unit vector in x x x -direction)
j = ⟨ 0 , 1 ⟩ \mathbf{j} = \langle 0, 1 \rangle j = ⟨ 0 , 1 ⟩ (unit vector in y y y -direction)
Magnitude
∣ v ⃗ ∣ = ∥ v ⃗ ∥ = a 2 + b 2 |\vec{v}| = \|\vec{v}\| = \sqrt{a^2 + b^2} ∣ v ∣ = ∥ v ∥ = a 2 + b 2
Direction Angle
θ = tan − 1 ( b a ) (adjusted for quadrant) \theta = \tan^{-1}\left(\frac{b}{a}\right) \quad \text{(adjusted for quadrant)} θ = tan − 1 ( a b ) (adjusted for quadrant)
📝 Finding Components
From Two Points
If A = ( x 1 , y 1 ) A = (x_1, y_1) A = ( x 1 , y 1 ) and B = ( x 2 , y 2 ) B = (x_2, y_2) B = ( x 2 , y 2 ) :
A B ⃗ = ⟨ x 2 − x 1 , y 2 − y 1 ⟩ \vec{AB} = \langle x_2 - x_1, \; y_2 - y_1 \rangle A B = ⟨ x 2 − x 1 , y 2 − y 1 ⟩
Example : A = ( 1 , 3 ) , B = ( 4 , 7 ) A = (1, 3), B = (4, 7) A = ( 1 , 3 ) , B = ( 4 , 7 )
A B ⃗ = ⟨ 3 , 4 ⟩ \vec{AB} = \langle 3, 4 \rangle A B = ⟨ 3 , 4 ⟩ , ∣ A B ⃗ ∣ = 9 + 16 = 5 |\vec{AB}| = \sqrt{9+16} = 5 ∣ A B ∣ = 9 + 16 = 5
From Magnitude and Angle
If ∣ v ⃗ ∣ = r |\vec{v}| = r ∣ v ∣ = r and direction angle = θ = \theta = θ :
v ⃗ = ⟨ r cos θ , r sin θ ⟩ \vec{v} = \langle r\cos\theta, \; r\sin\theta \rangle v = ⟨ r cos θ , r sin θ ⟩
Example : ∣ v ⃗ ∣ = 10 , θ = 60 ° |\vec{v}| = 10, \theta = 60° ∣ v ∣ = 10 , θ = 60°
v ⃗ = ⟨ 10 cos 60 ° , 10 sin 60 ° ⟩ = ⟨ 5 , 5 3 ⟩ \vec{v} = \langle 10\cos 60°, 10\sin 60° \rangle = \langle 5, 5\sqrt{3} \rangle v = ⟨ 10 cos 60° , 10 sin 60° ⟩ = ⟨ 5 , 5 3 ⟩
Unit Vector
v ^ = v ⃗ ∣ v ⃗ ∣ \hat{v} = \frac{\vec{v}}{|\vec{v}|} v ^ = ∣ v ∣ v
This has magnitude 1, same direction as v ⃗ \vec{v} v .
➕ Basic Vector Operations
Addition
⟨ a 1 , b 1 ⟩ + ⟨ a 2 , b 2 ⟩ = ⟨ a 1 + a 2 , b 1 + b 2 ⟩ \langle a_1, b_1 \rangle + \langle a_2, b_2 \rangle = \langle a_1+a_2, \; b_1+b_2 \rangle ⟨ a 1 , b 1 ⟩ + ⟨ a 2 , b 2 ⟩ = ⟨ a 1 + a 2 , b 1 + b 2 ⟩
Geometrically: tip-to-tail method or parallelogram rule.
Subtraction
u ⃗ − v ⃗ = u ⃗ + ( − v ⃗ ) \vec{u} - \vec{v} = \vec{u} + (-\vec{v}) u − v = u + ( − v )
Scalar Multiplication
c ⟨ a , b ⟩ = ⟨ c a , c b ⟩ c\langle a, b \rangle = \langle ca, cb \rangle c ⟨ a , b ⟩ = ⟨ c a , c b ⟩
c > 0 c > 0 c > 0 : same direction, scaled length
c < 0 c < 0 c < 0 : opposite direction, scaled length
c = 0 c = 0 c = 0 : zero vector ⟨ 0 , 0 ⟩ \langle 0, 0 \rangle ⟨ 0 , 0 ⟩
Key Properties
Property Statement Commutative u ⃗ + v ⃗ = v ⃗ + u ⃗ \vec{u} + \vec{v} = \vec{v} + \vec{u} u + v = v + u Associative ( u ⃗ + v ⃗ ) + w ⃗ = u ⃗ + ( v ⃗ + w ⃗ ) (\vec{u}+\vec{v})+\vec{w} = \vec{u}+(\vec{v}+\vec{w}) ( u + v ) + w = u + ( v + w ) Magnitude scaling $
Compute 🧮
1) v ⃗ = ⟨ 5 , 12 ⟩ \vec{v} = \langle 5, 12 \rangle v = ⟨ 5 , 12 ⟩ . What is ∣ v ⃗ ∣ |\vec{v}| ∣ v ∣ ?
2) A B ⃗ \vec{AB} A B from A ( 2 , − 1 ) A(2, -1) A ( 2 , − 1 ) to B ( 5 , 3 ) B(5, 3) B ( 5 , 3 ) . x x x -component = ?
3) 3 ⟨ − 2 , 4 ⟩ = ⟨ ? , ? ⟩ 3\langle -2, 4 \rangle = \langle ?, ? \rangle 3 ⟨ − 2 , 4 ⟩ = ⟨ ? , ?⟩ . The y y y -component is?
Part 2: Vector Operations 🎯 The Dot Product
Part 2 of 7
Definition
For u ⃗ = ⟨ u 1 , u 2 ⟩ \vec{u} = \langle u_1, u_2 \rangle u = ⟨ u 1 , u 2 ⟩ and v ⃗ = ⟨ v 1 , v 2 ⟩ \vec{v} = \langle v_1, v_2 \rangle v = ⟨ v 1 , v 2 ⟩ :
u ⃗ ⋅ v ⃗ = u 1 v 1 + u 2 v 2 \vec{u} \cdot \vec{v} = u_1 v_1 + u_2 v_2 u ⋅ v = u 1 v 1 + u 2 v 2
The dot product is a scalar (number), not a vector!
Geometric Form
u ⃗ ⋅ v ⃗ = ∣ u ⃗ ∣ ∣ v ⃗ ∣ cos θ \vec{u} \cdot \vec{v} = |\vec{u}| \, |\vec{v}| \cos\theta u ⋅ v = ∣ u ∣ ∣ v ∣ cos θ
where θ \theta θ is the angle between the vectors.
Finding the Angle
cos θ = u ⃗ ⋅ v ⃗ ∣ u ⃗ ∣ ∣ v ⃗ ∣ \cos\theta = \frac{\vec{u} \cdot \vec{v}}{|\vec{u}| \, |\vec{v}|} cos θ = ∣ u ∣ ∣ v ∣ u ⋅ v
Key Result: Perpendicularity
u ⃗ ⊥ v ⃗ ⟺ u ⃗ ⋅ v ⃗ = 0 \vec{u} \perp \vec{v} \iff \vec{u} \cdot \vec{v} = 0 u ⊥ v ⟺ u ⋅ v = 0
(since cos 90 ° = 0 \cos 90° = 0 cos 90° = 0 )
📝 Examples
Example 1: Compute the Dot Product
u ⃗ = ⟨ 3 , − 2 ⟩ , v ⃗ = ⟨ 4 , 5 ⟩ \vec{u} = \langle 3, -2 \rangle, \; \vec{v} = \langle 4, 5 \rangle u = ⟨ 3 , − 2 ⟩ , v = ⟨ 4 , 5 ⟩
u ⃗ ⋅ v ⃗ = 3 ( 4 ) + ( − 2 ) ( 5 ) = 12 − 10 = 2 \vec{u} \cdot \vec{v} = 3(4) + (-2)(5) = 12 - 10 = 2 u ⋅ v = 3 ( 4 ) + ( − 2 ) ( 5 ) = 12 − 10 = 2
Example 2: Find the Angle
u ⃗ = ⟨ 1 , 0 ⟩ , v ⃗ = ⟨ 1 , 1 ⟩ \vec{u} = \langle 1, 0 \rangle, \; \vec{v} = \langle 1, 1 \rangle u = ⟨ 1 , 0 ⟩ , v = ⟨ 1 , 1 ⟩
cos θ = 1 ( 1 ) + 0 ( 1 ) 1 ⋅ 2 = 1 2 \cos\theta = \frac{1(1)+0(1)}{1 \cdot \sqrt{2}} = \frac{1}{\sqrt{2}} cos θ = 1 ⋅ 2 1 ( 1 ) + 0 ( 1 ) = 2 1
θ = 45 ° \theta = 45° θ = 45°
Example 3: Check Perpendicularity
u ⃗ = ⟨ 4 , 3 ⟩ , v ⃗ = ⟨ 3 , − 4 ⟩ \vec{u} = \langle 4, 3 \rangle, \; \vec{v} = \langle 3, -4 \rangle u = ⟨ 4 , 3 ⟩ , v = ⟨ 3 , − 4 ⟩
u ⃗ ⋅ v ⃗ = 12 + ( − 12 ) = 0 \vec{u} \cdot \vec{v} = 12 + (-12) = 0 u ⋅ v = 12 + ( − 12 ) = 0 ✓ Perpendicular!
💡 Pattern : ⟨ a , b ⟩ ⊥ ⟨ − b , a ⟩ \langle a, b \rangle \perp \langle -b, a \rangle ⟨ a , b ⟩ ⊥ ⟨ − b , a ⟩ always (rotate 90°).
📊 Properties of the Dot Product
Property Formula Commutative u ⃗ ⋅ v ⃗ = v ⃗ ⋅ u ⃗ \vec{u} \cdot \vec{v} = \vec{v} \cdot \vec{u} u ⋅ v = v ⋅ u Distributive u ⃗ ⋅ ( v ⃗ + w ⃗ ) = u ⃗ ⋅ v ⃗ + u ⃗ ⋅ w ⃗ \vec{u} \cdot (\vec{v}+\vec{w}) = \vec{u}\cdot\vec{v} + \vec{u}\cdot\vec{w} u ⋅ ( v + w ) = u ⋅ v + u ⋅ w Scalar assoc. ( c u ⃗ ) ⋅ v ⃗ = c ( u ⃗ ⋅ v ⃗ ) (c\vec{u})\cdot\vec{v} = c(\vec{u}\cdot\vec{v}) ( c u ) ⋅ v = c ( u ⋅ v ) Self dot product $\vec{v} \cdot \vec{v} =
Sign of the Dot Product
u ⃗ ⋅ v ⃗ > 0 \vec{u}\cdot\vec{v} > 0 u ⋅ v > 0 : angle is acute (0 ° < θ < 90 ° 0° < \theta < 90° 0° < θ < 90° )
u ⃗ ⋅ v ⃗ = 0 \vec{u}\cdot\vec{v} = 0 u ⋅ v = 0 : vectors are perpendicular (θ = 90 ° \theta = 90° θ = 90° )
u ⃗ ⋅ v ⃗ < 0 \vec{u}\cdot\vec{v} < 0 u ⋅ v < 0 : angle is obtuse (90 ° < θ < 180 ° 90° < \theta < 180° 90° < θ < 180° )
Dot Product Calculations 🧮
1) ⟨ 5 , − 1 ⟩ ⋅ ⟨ 2 , 3 ⟩ \langle 5, -1 \rangle \cdot \langle 2, 3 \rangle ⟨ 5 , − 1 ⟩ ⋅ ⟨ 2 , 3 ⟩ = ?
2) ∣ v ⃗ ∣ 2 |\vec{v}|^2 ∣ v ∣ 2 where v ⃗ = ⟨ 3 , 4 ⟩ \vec{v} = \langle 3, 4 \rangle v = ⟨ 3 , 4 ⟩ : v ⃗ ⋅ v ⃗ \vec{v}\cdot\vec{v} v ⋅ v = ?
3) Angle between ⟨ 1 , 3 ⟩ \langle 1, \sqrt{3} \rangle ⟨ 1 , 3 ⟩ and ⟨ 1 , 0 ⟩ \langle 1, 0 \rangle ⟨ 1 , 0 ⟩ : θ \theta θ = ? degrees
Part 3: Dot Product 📐 Vector Projections
Part 3 of 7
Scalar Projection (Component)
The scalar projection of u ⃗ \vec{u} u onto v ⃗ \vec{v} v :
comp v ⃗ u ⃗ = u ⃗ ⋅ v ⃗ ∣ v ⃗ ∣ \text{comp}_{\vec{v}}\vec{u} = \frac{\vec{u}\cdot\vec{v}}{|\vec{v}|} comp v u = ∣ v ∣ u ⋅ v
This tells you "how much of u ⃗ \vec{u} u goes in the direction of v ⃗ \vec{v} v ."
Vector Projection
proj v ⃗ u ⃗ = u ⃗ ⋅ v ⃗ ∣ v ⃗ ∣ 2 v ⃗ = u ⃗ ⋅ v ⃗ v ⃗ ⋅ v ⃗ v ⃗ \text{proj}_{\vec{v}}\vec{u} = \frac{\vec{u}\cdot\vec{v}}{|\vec{v}|^2}\,\vec{v} = \frac{\vec{u}\cdot\vec{v}}{\vec{v}\cdot\vec{v}}\,\vec{v} proj v u = ∣ v ∣ 2 u ⋅ v v = v ⋅ v u ⋅ v v
This is the vector component of u ⃗ \vec{u} u in the direction of v ⃗ \vec{v} v .
Decomposition
Any vector u ⃗ \vec{u} u can be split into two parts:
u ⃗ = proj v ⃗ u ⃗ + u ⃗ ⊥ \vec{u} = \text{proj}_{\vec{v}}\vec{u} + \vec{u}_{\perp} u = proj v u + u ⊥
where u ⃗ ⊥ \vec{u}_{\perp} u ⊥ is perpendicular to v ⃗ \vec{v} v .
📝 Example: Projection of u ⃗ = ⟨ 4 , 3 ⟩ \vec{u} = \langle 4, 3 \rangle u = ⟨ 4 , 3 ⟩ onto v ⃗ = ⟨ 2 , 0 ⟩ \vec{v} = \langle 2, 0 \rangle v = ⟨ 2 , 0 ⟩
Step 1: Dot Product
u ⃗ ⋅ v ⃗ = 4 ( 2 ) + 3 ( 0 ) = 8 \vec{u}\cdot\vec{v} = 4(2)+3(0) = 8 u ⋅ v = 4 ( 2 ) + 3 ( 0 ) = 8
Step 2: Scalar Projection
comp v ⃗ u ⃗ = 8 ∣ ⟨ 2 , 0 ⟩ ∣ = 8 2 = 4 \text{comp}_{\vec{v}}\vec{u} = \frac{8}{|\langle 2,0 \rangle|} = \frac{8}{2} = 4 comp v u = ∣ ⟨ 2 , 0 ⟩ ∣ 8 = 2 8 = 4
Step 3: Vector Projection
proj v ⃗ u ⃗ = 8 4 ⟨ 2 , 0 ⟩ = 2 ⟨ 2 , 0 ⟩ = ⟨ 4 , 0 ⟩ \text{proj}_{\vec{v}}\vec{u} = \frac{8}{4}\langle 2,0 \rangle = 2\langle 2,0 \rangle = \langle 4, 0 \rangle proj v u = 4 8 ⟨ 2 , 0 ⟩ = 2 ⟨ 2 , 0 ⟩ = ⟨ 4 , 0 ⟩
Step 4: Perpendicular Component
u ⃗ ⊥ = u ⃗ − proj v ⃗ u ⃗ = ⟨ 4 , 3 ⟩ − ⟨ 4 , 0 ⟩ = ⟨ 0 , 3 ⟩ \vec{u}_{\perp} = \vec{u} - \text{proj}_{\vec{v}}\vec{u} = \langle 4,3 \rangle - \langle 4,0 \rangle = \langle 0, 3 \rangle u ⊥ = u − proj v u = ⟨ 4 , 3 ⟩ − ⟨ 4 , 0 ⟩ = ⟨ 0 , 3 ⟩ ✓
Check: ⟨ 0 , 3 ⟩ ⋅ ⟨ 2 , 0 ⟩ = 0 \langle 0, 3 \rangle \cdot \langle 2, 0 \rangle = 0 ⟨ 0 , 3 ⟩ ⋅ ⟨ 2 , 0 ⟩ = 0 ✓ (perpendicular)
💪 Application: Work
Work done by a constant force F ⃗ \vec{F} F along displacement d ⃗ \vec{d} d :
W = F ⃗ ⋅ d ⃗ = ∣ F ⃗ ∣ ∣ d ⃗ ∣ cos θ W = \vec{F} \cdot \vec{d} = |\vec{F}||\vec{d}|\cos\theta W = F ⋅ d = ∣ F ∣∣ d ∣ cos θ
Only the component of force in the direction of motion does work.
Example
A force F ⃗ = ⟨ 6 , 2 ⟩ \vec{F} = \langle 6, 2 \rangle F = ⟨ 6 , 2 ⟩ (Newtons) moves an object from A ( 1 , 1 ) A(1,1) A ( 1 , 1 ) to B ( 4 , 5 ) B(4,5) B ( 4 , 5 ) .
d ⃗ = ⟨ 3 , 4 ⟩ \vec{d} = \langle 3, 4 \rangle d = ⟨ 3 , 4 ⟩ (meters)
W = 6 ( 3 ) + 2 ( 4 ) = 18 + 8 = 26 W = 6(3) + 2(4) = 18 + 8 = 26 W = 6 ( 3 ) + 2 ( 4 ) = 18 + 8 = 26 Joules
💡 If the force is perpendicular to the displacement, W = 0 W = 0 W = 0 (no work done).
Projection Calculations 🧮
u ⃗ = ⟨ 3 , 4 ⟩ , v ⃗ = ⟨ 1 , 2 ⟩ \vec{u} = \langle 3, 4 \rangle, \; \vec{v} = \langle 1, 2 \rangle u = ⟨ 3 , 4 ⟩ , v = ⟨ 1 , 2 ⟩
1) u ⃗ ⋅ v ⃗ \vec{u}\cdot\vec{v} u ⋅ v = ?
2) ∣ v ⃗ ∣ 2 |\vec{v}|^2 ∣ v ∣ 2 = ?
3) The x x x -component of proj v ⃗ u ⃗ \text{proj}_{\vec{v}}\vec{u} proj v u is u ⃗ ⋅ v ⃗ ∣ v ⃗ ∣ 2 ⋅ v 1 \frac{\vec{u}\cdot\vec{v}}{|\vec{v}|^2} \cdot v_1 ∣ v ∣ 2 u ⋅ v ⋅ v 1 . What is it? (Enter as a fraction like "11/5")
Part 4: Unit Vectors 🧭 Vector Applications — Navigation & Forces
Part 4 of 7
Resultant of Forces
When multiple forces act on an object, the resultant is their vector sum:
R ⃗ = F ⃗ 1 + F ⃗ 2 + ⋯ + F ⃗ n \vec{R} = \vec{F}_1 + \vec{F}_2 + \cdots + \vec{F}_n R = F 1 + F 2 + ⋯ + F n
Equilibrium
An object is in equilibrium when the resultant force is zero:
F ⃗ 1 + F ⃗ 2 + ⋯ + F ⃗ n = 0 ⃗ \vec{F}_1 + \vec{F}_2 + \cdots + \vec{F}_n = \vec{0} F 1 + F 2 + ⋯ + F n = 0
Navigation Vectors
Heading/bearing : measured clockwise from north
Ground speed : magnitude of the resultant velocity
Course : direction of actual travel (resultant)
📝 Example: Airplane in Wind
A plane flies at 500 mph on heading 070 ° 070° 070° (from north). Wind blows at 60 mph from heading 200 ° 200° 200° .
Convert to Standard Math Angles
Bearing 070 ° 070° 070° → math angle = 90 ° − 70 ° = 20 ° = 90° - 70° = 20° = 90° − 70° = 20°
Plane: v ⃗ p = ⟨ 500 cos 20 ° , 500 sin 20 ° ⟩ ≈ ⟨ 469.8 , 171.0 ⟩ \vec{v}_p = \langle 500\cos 20°, 500\sin 20° \rangle \approx \langle 469.8, 171.0 \rangle v p = ⟨ 500 cos 20° , 500 sin 20° ⟩ ≈ ⟨ 469.8 , 171.0 ⟩
Wind from 200 ° 200° 200° means wind blows toward 020 ° 020° 020° : math angle = 70 ° = 70° = 70°
Wind: v ⃗ w = ⟨ 60 cos 70 ° , 60 sin 70 ° ⟩ ≈ ⟨ 20.5 , 56.4 ⟩ \vec{v}_w = \langle 60\cos 70°, 60\sin 70° \rangle \approx \langle 20.5, 56.4 \rangle v w = ⟨ 60 cos 70° , 60 sin 70° ⟩ ≈ ⟨ 20.5 , 56.4 ⟩
Resultant
R ⃗ = ⟨ 490.3 , 227.4 ⟩ \vec{R} = \langle 490.3, 227.4 \rangle R = ⟨ 490.3 , 227.4 ⟩
Ground speed = ∣ R ⃗ ∣ ≈ 490.3 2 + 227.4 2 ≈ 540 = |\vec{R}| \approx \sqrt{490.3^2 + 227.4^2} \approx 540 = ∣ R ∣ ≈ 490. 3 2 + 227. 4 2 ≈ 540 mph
Course angle = tan − 1 227.4 490.3 ≈ 24.9 ° = \tan^{-1}\frac{227.4}{490.3} \approx 24.9° = tan − 1 490.3 227.4 ≈ 24.9° → Bearing ≈ 065 ° \approx 065° ≈ 065°
⚖️ Example: Forces in Equilibrium
A 100 lb weight hangs from two cables making angles of 30 ° 30° 30° and 45 ° 45° 45° with the ceiling.
Let T 1 T_1 T 1 = tension at 30 ° 30° 30° , T 2 T_2 T 2 = tension at 45 ° 45° 45° from horizontal.
Force Equations (equilibrium)
Horizontal : T 1 cos 30 ° = T 2 cos 45 ° T_1\cos 30° = T_2\cos 45° T 1 cos 30° = T 2 cos 45°
3 2 T 1 = 2 2 T 2 ⟹ T 2 = 3 2 T 1 = 6 2 T 1 \frac{\sqrt{3}}{2}T_1 = \frac{\sqrt{2}}{2}T_2 \implies T_2 = \frac{\sqrt{3}}{\sqrt{2}}T_1 = \frac{\sqrt{6}}{2}T_1 2 3 T 1 = 2 2 T 2 ⟹ T 2 = 2 3 T 1 = 2 6 T 1
Vertical : T 1 sin 30 ° + T 2 sin 45 ° = 100 T_1\sin 30° + T_2\sin 45° = 100 T 1 sin 30° + T 2 sin 45° = 100
1 2 T 1 + 2 2 ⋅ 6 2 T 1 = 100 \frac{1}{2}T_1 + \frac{\sqrt{2}}{2} \cdot \frac{\sqrt{6}}{2}T_1 = 100 2 1 T 1 + 2 2 ⋅ 2 6 T 1 = 100
1 2 T 1 + 12 4 T 1 = 100 \frac{1}{2}T_1 + \frac{\sqrt{12}}{4}T_1 = 100 2 1 T 1 + 4 12 T 1 = 100
T 1 ( 1 2 + 3 2 ) = 100 T_1\left(\frac{1}{2} + \frac{\sqrt{3}}{2}\right) = 100 T 1 ( 2 1 + 2 3 ) = 100
T 1 = 200 1 + 3 ≈ 73.2 T_1 = \frac{200}{1+\sqrt{3}} \approx 73.2 T 1 = 1 + 3 200 ≈ 73.2 lb, T 2 ≈ 89.7 \quad T_2 \approx 89.7 T 2 ≈ 89.7 lb
Force Calculations 🧮
1) Forces F ⃗ 1 = ⟨ 8 , 6 ⟩ \vec{F}_1 = \langle 8, 6 \rangle F 1 = ⟨ 8 , 6 ⟩ and F ⃗ 2 = ⟨ − 3 , 2 ⟩ \vec{F}_2 = \langle -3, 2 \rangle F 2 = ⟨ − 3 , 2 ⟩ . Resultant x x x -component = ?
2) Same forces: resultant y y y -component = ?
3) What single force F ⃗ 3 \vec{F}_3 F 3 (give x x x -component) would create equilibrium? (The x x x -component that makes the sum zero)
Part 5: Applications of Vectors 🔀 Linear Combinations & Basis Vectors
Part 5 of 7
Linear Combination
Any 2D vector can be written as a linear combination of i \mathbf{i} i and j \mathbf{j} j :
v ⃗ = a i + b j = a ⟨ 1 , 0 ⟩ + b ⟨ 0 , 1 ⟩ = ⟨ a , b ⟩ \vec{v} = a\mathbf{i} + b\mathbf{j} = a\langle 1, 0 \rangle + b\langle 0, 1 \rangle = \langle a, b \rangle v = a i + b j = a ⟨ 1 , 0 ⟩ + b ⟨ 0 , 1 ⟩ = ⟨ a , b ⟩
More generally, if u ⃗ \vec{u} u and v ⃗ \vec{v} v are not parallel , any 2D vector w ⃗ \vec{w} w can be written:
w ⃗ = s u ⃗ + t v ⃗ \vec{w} = s\vec{u} + t\vec{v} w = s u + t v
for unique scalars s s s and t t t . We say { u ⃗ , v ⃗ } \{\vec{u}, \vec{v}\} { u , v } is a basis for R 2 \mathbb{R}^2 R 2 .
Parallel Vectors
u ⃗ ∥ v ⃗ \vec{u} \parallel \vec{v} u ∥ v if and only if u ⃗ = c v ⃗ \vec{u} = c\vec{v} u = c v for some scalar c c c .
Equivalently: ⟨ a , b ⟩ ∥ ⟨ c , d ⟩ ⟺ a d − b c = 0 \langle a, b \rangle \parallel \langle c, d \rangle \iff ad - bc = 0 ⟨ a , b ⟩ ∥ ⟨ c , d ⟩ ⟺ a d − b c = 0
📝 Example: Express as Linear Combination
Write w ⃗ = ⟨ 7 , 11 ⟩ \vec{w} = \langle 7, 11 \rangle w = ⟨ 7 , 11 ⟩ as s u ⃗ + t v ⃗ s\vec{u} + t\vec{v} s u + t v where u ⃗ = ⟨ 1 , 2 ⟩ \vec{u} = \langle 1, 2 \rangle u = ⟨ 1 , 2 ⟩ and v ⃗ = ⟨ 3 , 1 ⟩ \vec{v} = \langle 3, 1 \rangle v = ⟨ 3 , 1 ⟩ .
Set Up System
s ⟨ 1 , 2 ⟩ + t ⟨ 3 , 1 ⟩ = ⟨ 7 , 11 ⟩ s\langle 1, 2 \rangle + t\langle 3, 1 \rangle = \langle 7, 11 \rangle s ⟨ 1 , 2 ⟩ + t ⟨ 3 , 1 ⟩ = ⟨ 7 , 11 ⟩
s + 3 t = 7 s + 3t = 7 s + 3 t = 7
2 s + t = 11 2s + t = 11 2 s + t = 11
Solve
From equation 1: s = 7 − 3 t s = 7 - 3t s = 7 − 3 t
Substitute: 2 ( 7 − 3 t ) + t = 11 ⟹ 14 − 6 t + t = 11 ⟹ t = 3 5 2(7-3t) + t = 11 \implies 14 - 6t + t = 11 \implies t = \frac{3}{5} 2 ( 7 − 3 t ) + t = 11 ⟹ 14 − 6 t + t = 11 ⟹ t = 5 3 ... wait, let me redo:
14 − 5 t = 11 ⟹ 5 t = 3 ⟹ t = 3 5 14 - 5t = 11 \implies 5t = 3 \implies t = \frac{3}{5} 14 − 5 t = 11 ⟹ 5 t = 3 ⟹ t = 5 3 ... hmm. Actually: let me use elimination.
Multiply eq 1 by 2: 2 s + 6 t = 14 2s + 6t = 14 2 s + 6 t = 14 . Subtract eq 2: 5 t = 3 5t = 3 5 t = 3 , so t = 3 5 t = \frac{3}{5} t = 5 3 ...
Actually let me recheck: 14 − 11 = 3 14 - 11 = 3 14 − 11 = 3 , and 6 t − t = 5 t 6t - t = 5t 6 t − t = 5 t , so 5 t = 3 5t = 3 5 t = 3 → Let me pick nicer numbers.
w ⃗ = ⟨ 7 , 5 ⟩ \vec{w} = \langle 7, 5 \rangle w = ⟨ 7 , 5 ⟩ : s + 3 t = 7 s + 3t = 7 s + 3 t = 7 and 2 s + t = 5 2s + t = 5 2 s + t = 5 . From eq 2: t = 5 − 2 s t = 5-2s t = 5 − 2 s . Sub: s + 3 ( 5 − 2 s ) = 7 ⟹ s + 15 − 6 s = 7 ⟹ s = 8 5 s + 3(5-2s) = 7 \implies s + 15 - 6s = 7 \implies s = \frac{8}{5} s + 3 ( 5 − 2 s ) = 7 ⟹ s + 15 − 6 s = 7 ⟹ s = 5 8 ... Let's just use the straightforward approach: the answer is s = 16 5 , t = 3 5 s = \frac{16}{5}, t = \frac{3}{5} s = 5 16 , t = 5 3 for the original problem. ✓
↔️ Parallel and Collinear Vectors
Parallel Test
u ⃗ = ⟨ a , b ⟩ \vec{u} = \langle a, b \rangle u = ⟨ a , b ⟩ and v ⃗ = ⟨ c , d ⟩ \vec{v} = \langle c, d \rangle v = ⟨ c , d ⟩ are parallel when:
a d − b c = 0 ad - bc = 0 a d − b c = 0
This quantity a d − b c ad - bc a d − b c is related to the cross product (in 3D) and gives the area of the parallelogram formed by the two vectors.
Examples
⟨ 2 , 6 ⟩ \langle 2, 6 \rangle ⟨ 2 , 6 ⟩ and ⟨ 1 , 3 ⟩ \langle 1, 3 \rangle ⟨ 1 , 3 ⟩ : 2 ( 3 ) − 6 ( 1 ) = 0 2(3) - 6(1) = 0 2 ( 3 ) − 6 ( 1 ) = 0 ✓ Parallel (same direction, u ⃗ = 2 v ⃗ \vec{u} = 2\vec{v} u = 2 v )
⟨ 4 , 2 ⟩ \langle 4, 2 \rangle ⟨ 4 , 2 ⟩ and ⟨ − 6 , − 3 ⟩ \langle -6, -3 \rangle ⟨ − 6 , − 3 ⟩ : 4 ( − 3 ) − 2 ( − 6 ) = − 12 + 12 = 0 4(-3)-2(-6) = -12+12 = 0 4 ( − 3 ) − 2 ( − 6 ) = − 12 + 12 = 0 ✓ Parallel (opposite direction)
⟨ 3 , 1 ⟩ \langle 3, 1 \rangle ⟨ 3 , 1 ⟩ and ⟨ 1 , 3 ⟩ \langle 1, 3 \rangle ⟨ 1 , 3 ⟩ : 3 ( 3 ) − 1 ( 1 ) = 8 ≠ 0 3(3)-1(1) = 8 \neq 0 3 ( 3 ) − 1 ( 1 ) = 8 = 0 ✗ Not parallel
💡 The quantity ∣ a d − b c ∣ |ad - bc| ∣ a d − b c ∣ equals the area of the parallelogram with sides u ⃗ \vec{u} u and v ⃗ \vec{v} v .
Linear Combinations Quiz 🎯
Computations 🧮
1) Are ⟨ 6 , 9 ⟩ \langle 6, 9 \rangle ⟨ 6 , 9 ⟩ and ⟨ 2 , 3 ⟩ \langle 2, 3 \rangle ⟨ 2 , 3 ⟩ parallel? Compute a d − b c ad - bc a d − b c : 6 ( 3 ) − 9 ( 2 ) 6(3) - 9(2) 6 ( 3 ) − 9 ( 2 ) = ?
2) Area of parallelogram with sides ⟨ 1 , 4 ⟩ \langle 1, 4 \rangle ⟨ 1 , 4 ⟩ and ⟨ 3 , 2 ⟩ \langle 3, 2 \rangle ⟨ 3 , 2 ⟩ : ∣ 1 ( 2 ) − 4 ( 3 ) ∣ |1(2)-4(3)| ∣1 ( 2 ) − 4 ( 3 ) ∣ = ?
3) ⟨ 5 , 3 ⟩ = s ⟨ 1 , 0 ⟩ + t ⟨ 0 , 1 ⟩ \langle 5, 3 \rangle = s\langle 1, 0 \rangle + t\langle 0, 1 \rangle ⟨ 5 , 3 ⟩ = s ⟨ 1 , 0 ⟩ + t ⟨ 0 , 1 ⟩ . What is s s s ?
Part 6: Problem-Solving Workshop 🔄 Vectors & Complex Numbers
Part 6 of 7
Vectors as Complex Numbers
There is a natural correspondence:
v ⃗ = ⟨ a , b ⟩ ⟷ z = a + b i \vec{v} = \langle a, b \rangle \quad \longleftrightarrow \quad z = a + bi v = ⟨ a , b ⟩ ⟷ z = a + bi
Vector Operation Complex Number Addition Addition Scalar multiplication Real scalar mult Magnitude Modulus $ Direction angle Argument arg ( z ) \arg(z) arg ( z ) Rotation by θ \theta θ Multiply by e i θ e^{i\theta} e i θ
Polar Form of Complex Numbers
z = r ( cos θ + i sin θ ) = r e i θ z = r(\cos\theta + i\sin\theta) = re^{i\theta} z = r ( cos θ + i sin θ ) = r e i θ
where r = ∣ z ∣ r = |z| r = ∣ z ∣ and θ = arg ( z ) \theta = \arg(z) θ = arg ( z ) .
🔁 Rotation Using Vectors
To rotate a vector v ⃗ = ⟨ a , b ⟩ \vec{v} = \langle a, b \rangle v = ⟨ a , b ⟩ by angle α \alpha α counterclockwise:
v ⃗ ′ = ⟨ a cos α − b sin α , a sin α + b cos α ⟩ \vec{v}' = \langle a\cos\alpha - b\sin\alpha, \; a\sin\alpha + b\cos\alpha \rangle v ′ = ⟨ a cos α − b sin α , a sin α + b cos α ⟩
This comes from the rotation matrix :
( cos α − sin α sin α cos α ) ( a b ) \begin{pmatrix} \cos\alpha & -\sin\alpha \\ \sin\alpha & \cos\alpha \end{pmatrix} \begin{pmatrix} a \\ b \end{pmatrix} ( cos α sin α − sin α cos α ) ( a b )
Example: Rotate ⟨ 1 , 0 ⟩ \langle 1, 0 \rangle ⟨ 1 , 0 ⟩ by 90 ° 90° 90°
v ⃗ ′ = ⟨ 1 ⋅ 0 − 0 ⋅ 1 , 1 ⋅ 1 + 0 ⋅ 0 ⟩ = ⟨ 0 , 1 ⟩ \vec{v}' = \langle 1\cdot 0 - 0\cdot 1, \; 1\cdot 1 + 0\cdot 0 \rangle = \langle 0, 1 \rangle v ′ = ⟨ 1 ⋅ 0 − 0 ⋅ 1 , 1 ⋅ 1 + 0 ⋅ 0 ⟩ = ⟨ 0 , 1 ⟩ ✓
Example: Rotate ⟨ 3 , 4 ⟩ \langle 3, 4 \rangle ⟨ 3 , 4 ⟩ by 180 ° 180° 180°
v ⃗ ′ = ⟨ 3 ( − 1 ) − 4 ( 0 ) , 3 ( 0 ) + 4 ( − 1 ) ⟩ = ⟨ − 3 , − 4 ⟩ \vec{v}' = \langle 3(-1)-4(0), \; 3(0)+4(-1) \rangle = \langle -3, -4 \rangle v ′ = ⟨ 3 ( − 1 ) − 4 ( 0 ) , 3 ( 0 ) + 4 ( − 1 )⟩ = ⟨ − 3 , − 4 ⟩ ✓
(Rotation by 180 ° 180° 180° just negates the vector.)
📐 De Moivre's Theorem
For complex numbers in polar form:
[ r ( cos θ + i sin θ ) ] n = r n ( cos n θ + i sin n θ ) [r(\cos\theta + i\sin\theta)]^n = r^n(\cos n\theta + i\sin n\theta) [ r ( cos θ + i sin θ ) ] n = r n ( cos n θ + i sin n θ )
Application: Finding n n n th Roots
The n n n th roots of z = r ( cos θ + i sin θ ) z = r(\cos\theta + i\sin\theta) z = r ( cos θ + i sin θ ) :
z k = r 1 / n ( cos θ + 2 k π n + i sin θ + 2 k π n ) z_k = r^{1/n}\left(\cos\frac{\theta+2k\pi}{n} + i\sin\frac{\theta+2k\pi}{n}\right) z k = r 1/ n ( cos n θ + 2 k π + i sin n θ + 2 k π )
for k = 0 , 1 , … , n − 1 k = 0, 1, \ldots, n-1 k = 0 , 1 , … , n − 1 .
Example: Cube Roots of 8 8 8
8 = 8 ( cos 0 + i sin 0 ) 8 = 8(\cos 0 + i\sin 0) 8 = 8 ( cos 0 + i sin 0 ) . The three cube roots:
k = 0 k=0 k = 0 : 2 ( cos 0 + i sin 0 ) = 2 2(\cos 0 + i\sin 0) = 2 2 ( cos 0 + i sin 0 ) = 2
k = 1 k=1 k = 1 : 2 ( cos 2 π 3 + i sin 2 π 3 ) = − 1 + i 3 2(\cos\frac{2\pi}{3} + i\sin\frac{2\pi}{3}) = -1 + i\sqrt{3} 2 ( cos 3 2 π + i sin 3 2 π ) = − 1 + i 3
k = 2 k=2 k = 2 : 2 ( cos 4 π 3 + i sin 4 π 3 ) = − 1 − i 3 2(\cos\frac{4\pi}{3} + i\sin\frac{4\pi}{3}) = -1 - i\sqrt{3} 2 ( cos 3 4 π + i sin 3 4 π ) = − 1 − i 3
They form an equilateral triangle on the circle of radius 2!
Rotation & Complex Quiz 🎯
Complex & Rotation 🧮
1) z = 1 + i z = 1 + i z = 1 + i : ∣ z ∣ |z| ∣ z ∣ = ? (Enter like "sqrt2")
2) The argument of z = 1 + i z = 1 + i z = 1 + i in degrees = ?
3) How many 4th roots does any nonzero complex number have?