o calculate the distance between two points in a Cartesian coordinate system, you can use the distance formula, which is derived from the Pythagorean theorem. If you have two points (x1,y1)(x_1, y_1)(x1,y1) and (x2,y2)(x_2, y_2)(x2,y2), the distance ddd between these points is given by the formula:
d=(x2−x1)2+(y2−y1)2d = \sqrt{(x_2 – x_1)^2 + (y_2 – y_1)^2}d=(x2−x1)2+(y2−y1)2
Steps to Use the Distance Formula:
- Identify the Coordinates: Determine the coordinates of the two points. For example, let’s say Point A is (x1,y1)(x_1, y_1)(x1,y1) and Point B is (x2,y2)(x_2, y_2)(x2,y2).
- Subtract the Coordinates: Find the difference in the x-coordinates and the y-coordinates:
- x2−x1x_2 – x_1x2−x1
- y2−y1y_2 – y_1y2−y1
- Square the Differences: Square each of the differences obtained in step 2:
- (x2−x1)2(x_2 – x_1)^2(x2−x1)2
- (y2−y1)2(y_2 – y_1)^2(y2−y1)2
- Add the Squares: Add the two squared values together.
- Take the Square Root: Finally, take the square root of the sum to find the distance.
Example Calculation:
Let’s calculate the distance between points A(1,2)A(1, 2)A(1,2) and B(4,6)B(4, 6)B(4,6).
- x1=1,y1=2x_1 = 1, y_1 = 2x1=1,y1=2
- x2=4,y2=6x_2 = 4, y_2 = 6x2=4,y2=6
- Calculate the differences:
- x2−x1=4−1=3x_2 – x_1 = 4 – 1 = 3x2−x1=4−1=3
- y2−y1=6−2=4y_2 – y_1 = 6 – 2 = 4y2−y1=6−2=4
- Square the differences:
- (3)2=9(3)^2 = 9(3)2=9
- (4)2=16(4)^2 = 16(4)2=16
- Add the squares:
- 9+16=259 + 16 = 259+16=25
- Take the square root:
- d=25=5d = \sqrt{25} = 5d=25=5
Thus, the distance between points A(1,2)A(1, 2)A(1,2) and B(4,6)B(4, 6)B(4,6) is 5 units.
If you have specific points you’d like to calculate the distance for, feel free to share!
4.3.2 Distance between two points
n this section, we will explore the concept of calculating the distance between two points in a Cartesian coordinate system.
Definition
The distance between two points in a two-dimensional space can be defined as the length of the straight line segment that connects them. This distance can be calculated using the distance formula derived from the Pythagorean theorem.
Distance Formula
For two points A(x1,y1)A(x_1, y_1)A(x1,y1) and B(x2,y2)B(x_2, y_2)B(x2,y2), the distance ddd between these points is given by:
d=(x2−x1)2+(y2−y1)2d = \sqrt{(x_2 – x_1)^2 + (y_2 – y_1)^2}d=(x2−x1)2+(y2−y1)2
Breakdown of the Formula
- Coordinates:
- (x1,y1)(x_1, y_1)(x1,y1): coordinates of point A.
- (x2,y2)(x_2, y_2)(x2,y2): coordinates of point B.
- Differences:
- (x2−x1)(x_2 – x_1)(x2−x1): horizontal distance (difference in x-coordinates).
- (y2−y1)(y_2 – y_1)(y2−y1): vertical distance (difference in y-coordinates).
- Square the Differences: Each difference is squared to ensure that we are dealing with positive values.
- Sum of Squares: The sum of the squared differences is taken.
- Square Root: Finally, the square root of the sum gives the straight-line distance between the two points.
Example Calculation
Let’s calculate the distance between points A(3,4)A(3, 4)A(3,4) and B(7,1)B(7, 1)B(7,1):
- Identify Coordinates:
- x1=3,y1=4x_1 = 3, y_1 = 4x1=3,y1=4
- x2=7,y2=1x_2 = 7, y_2 = 1x2=7,y2=1
- Calculate Differences:
- x2−x1=7−3=4x_2 – x_1 = 7 – 3 = 4x2−x1=7−3=4
- y2−y1=1−4=−3y_2 – y_1 = 1 – 4 = -3y2−y1=1−4=−3
- Square the Differences:
- (4)2=16(4)^2 = 16(4)2=16
- (−3)2=9(-3)^2 = 9(−3)2=9
- Sum the Squares:
- 16+9=2516 + 9 = 2516+9=25
- Square Root:
- d=25=5d = \sqrt{25} = 5d=25=5
Thus, the distance between points A(3,4)A(3, 4)A(3,4) and B(7,1)B(7, 1)B(7,1) is 5 units.
Applications
Understanding how to calculate the distance between points is fundamental in various fields, including:
- Geometry: To determine the length of line segments.
- Physics: To analyze motion and determine displacement.
- Computer Science: In algorithms for pathfinding and spatial analysis.
If there’s a specific aspect of this topic you would like to focus on or if you have further questions, feel free to ask!
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4.3.3 Direction Cosines and Ratios
Definition
Direction cosines are the cosines of the angles that a vector makes with the coordinate axes. They provide a way to describe the orientation of a vector in three-dimensional space.
Direction Cosines
For a vector v\mathbf{v}v represented in Cartesian coordinates as v=(vx,vy,vz)\mathbf{v} = (v_x, v_y, v_z)v=(vx,vy,vz), the direction cosines l,m,nl, m, nl,m,n are defined as follows:
l=vx∥v∥,m=vy∥v∥,n=vz∥v∥l = \frac{v_x}{\|\mathbf{v}\|}, \quad m = \frac{v_y}{\|\mathbf{v}\|}, \quad n = \frac{v_z}{\|\mathbf{v}\|}l=∥v∥vx,m=∥v∥vy,n=∥v∥vzWhere:
- ∥v∥=vx2+vy2+vz2\|\mathbf{v}\| = \sqrt{v_x^2 + v_y^2 + v_z^2}∥v∥=vx2+vy2+vz2 is the magnitude of the vector v\mathbf{v}v.
- l,m,nl, m, nl,m,n are the direction cosines corresponding to the x, y, and z axes, respectively.
Properties of Direction Cosines
- Range: The direction cosines always satisfy the equation:l2+m2+n2=1l^2 + m^2 + n^2 = 1l2+m2+n2=1This relationship arises because they represent the components of a unit vector.
- Angles: If θx,θy,θz\theta_x, \theta_y, \theta_zθx,θy,θz are the angles between the vector and the x, y, and z axes respectively, then:l=cos(θx),m=cos(θy),n=cos(θz)l = \cos(\theta_x), \quad m = \cos(\theta_y), \quad n = \cos(\theta_z)l=cos(θx),m=cos(θy),n=cos(θz)
Direction Ratios
Direction ratios are proportional values that indicate the direction of a line in space. For a line represented by the vector v=(a,b,c)\mathbf{v} = (a, b, c)v=(a,b,c), the direction ratios are a,b,ca, b, ca,b,c. Unlike direction cosines, direction ratios do not need to be normalized and can be any set of proportional numbers.
Relationship Between Direction Cosines and Direction Ratios
If a,b,ca, b, ca,b,c are the direction ratios of a line, the corresponding direction cosines l,m,nl, m, nl,m,n can be expressed as:
l=aa2+b2+c2,m=ba2+b2+c2,n=ca2+b2+c2l = \frac{a}{\sqrt{a^2 + b^2 + c^2}}, \quad m = \frac{b}{\sqrt{a^2 + b^2 + c^2}}, \quad n = \frac{c}{\sqrt{a^2 + b^2 + c^2}}l=a2+b2+c2a,m=a2+b2+c2b,n=a2+b2+c2c
Example
Consider a vector v=(3,4,5)\mathbf{v} = (3, 4, 5)v=(3,4,5).
- Calculate Magnitude:∥v∥=32+42+52=9+16+25=50=52\|\mathbf{v}\| = \sqrt{3^2 + 4^2 + 5^2} = \sqrt{9 + 16 + 25} = \sqrt{50} = 5\sqrt{2}∥v∥=32+42+52=9+16+25=50=52
- Direction Cosines:l=352,m=452,n=552=12l = \frac{3}{5\sqrt{2}}, \quad m = \frac{4}{5\sqrt{2}}, \quad n = \frac{5}{5\sqrt{2}} = \frac{1}{\sqrt{2}}l=523,m=524,n=525=21
- Direction Ratios: The direction ratios for this vector are simply (3,4,5)(3, 4, 5)(3,4,5).
Applications
- Physics: To describe the orientation of forces and velocities.
- Engineering: For structural analysis and determining load directions.
- Computer Graphics: In 3D modeling and rendering to manipulate object orientations.
4.3.4 ProjectionProjection refers to the operation of mapping a vector onto another vector or onto a line or plane in a specific direction. This concept is fundamental in vector analysis and has numerous applications in physics, engineering, and computer graphics.
Types of Projections
- Projection of a Vector onto Another Vector:
- The projection of vector a\mathbf{a}a onto vector b\mathbf{b}b is a vector that represents how much of a\mathbf{a}a lies in the direction of b\mathbf{b}b.
- The formula for the projection of a\mathbf{a}a onto b\mathbf{b}b is given by:
projba=a⋅bb⋅bb\text{proj}_{\mathbf{b}} \mathbf{a} = \frac{\mathbf{a} \cdot \mathbf{b}}{\mathbf{b} \cdot \mathbf{b}} \mathbf{b}projba=b⋅ba⋅bbWhere:
- a⋅b\mathbf{a} \cdot \mathbf{b}a⋅b is the dot product of a\mathbf{a}a and b\mathbf{b}b.
- b⋅b\mathbf{b} \cdot \mathbf{b}b⋅b is the dot product of b\mathbf{b}b with itself, giving the square of its magnitude.
- Orthogonal Projection:
- The orthogonal projection refers specifically to the projection of a vector onto a line or a plane, where the resulting projection is perpendicular to that line or plane.
Example: Projection of a Vector onto Another Vector
Let’s say we have two vectors:
- a=(2,3)\mathbf{a} = (2, 3)a=(2,3)
- b=(4,1)\mathbf{b} = (4, 1)b=(4,1)
- Calculate the Dot Products:
- a⋅b=2⋅4+3⋅1=8+3=11\mathbf{a} \cdot \mathbf{b} = 2 \cdot 4 + 3 \cdot 1 = 8 + 3 = 11a⋅b=2⋅4+3⋅1=8+3=11
- b⋅b=4⋅4+1⋅1=16+1=17\mathbf{b} \cdot \mathbf{b} = 4 \cdot 4 + 1 \cdot 1 = 16 + 1 = 17b⋅b=4⋅4+1⋅1=16+1=17
- Compute the Projection:
- Using the projection formula:
projba=1117b=1117(4,1)=(4417,1117)\text{proj}_{\mathbf{b}} \mathbf{a} = \frac{11}{17} \mathbf{b} = \frac{11}{17} (4, 1) = \left(\frac{44}{17}, \frac{11}{17}\right)projba=1711b=1711(4,1)=(1744,1711)
- Interpretation:
- The resulting vector (4417,1117)\left(\frac{44}{17}, \frac{11}{17}\right)(1744,1711) represents the component of vector a\mathbf{a}a that lies in the direction of vector b\mathbf{b}b.
Applications of Projections
- Physics: To resolve forces into components along specific directions.
- Computer Graphics: To simulate the effects of perspective by projecting 3D points onto a 2D screen.
- Statistics: In regression analysis, projecting data points onto a line of best fit.
Summary
Projection is a vital concept in understanding how vectors relate to one another and how to decompose vectors into meaningful components. By projecting one vector onto another, we can analyze their relationships and understand their interactions in various contexts.