The formula for calculating the length of a vector in space. How to find the coordinates of a vector

First of all, you need to understand the very concept of a vector. In order to introduce the definition of a geometric vector, let us recall what a segment is. Let us introduce the following definition.

Definition 1

A segment is a part of a straight line that has two boundaries in the form of points.

A segment can have 2 directions. To indicate the direction, we will call one of the boundaries of the segment its beginning, and the other boundary - its end. The direction is indicated from its beginning to the end of the segment.

Definition 2

A vector or a directed segment is a segment for which it is known which of the boundaries of the segment is considered the beginning and which is its end.

Designation: Two letters: $ \\ overline (AB) $ - (where $ A $ is its beginning and $ B $ is its end).

One small letter: $ \\ overline (a) $ (fig. 1).

Let us now introduce directly the concept of vector lengths.

Definition 3

The length of the vector $ \\ overline (a) $ is the length of the segment $ a $.

Notation: $ | \\ overline (a) | $

The concept of the length of a vector is associated, for example, with such a concept as the equality of two vectors.

Definition 4

Two vectors will be called equal if they satisfy two conditions: 1. They are co-directed; 1. Their lengths are equal (Fig. 2).

In order to define vectors, a coordinate system is introduced and coordinates for the vector in the entered system are determined. As we know, any vector can be expanded as $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $, where $ m $ and $ n $ are real numbers, and $ \\ overline (i ) $ and $ \\ overline (j) $ are unit vectors on the $ Ox $ and $ Oy $ axes, respectively.

Definition 5

The expansion coefficients of the vector $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $ will be called the coordinates of this vector in the introduced coordinate system. Mathematically:

$ \\ overline (c) \u003d (m, n) $

How do I find the length of a vector?

In order to derive a formula for calculating the length of an arbitrary vector from its given coordinates, consider the following problem:

Example 1

Given: vector $ \\ overline (α) $ with coordinates $ (x, y) $. Find: the length of this vector.

Let us introduce the Cartesian coordinate system $ xOy $ on the plane. Set aside $ \\ overline (OA) \u003d \\ overline (a) $ from the origin of the introduced coordinate system. Let us construct projections $ OA_1 $ and $ OA_2 $ of the constructed vector on the axes $ Ox $ and $ Oy $, respectively (Fig. 3).

The vector $ \\ overline (OA) $ constructed by us will be the radius vector for the point $ A $, therefore, it will have coordinates $ (x, y) $, which means

$ \u003d x $, $ [OA_2] \u003d y $

Now we can easily find the required length using the Pythagorean theorem, we get

$ | \\ overline (α) | ^ 2 \u003d ^ 2 + ^ 2 $

$ | \\ overline (α) | ^ 2 \u003d x ^ 2 + y ^ 2 $

$ | \\ overline (α) | \u003d \\ sqrt (x ^ 2 + y ^ 2) $

Answer: $ \\ sqrt (x ^ 2 + y ^ 2) $.

Conclusion:To find the length of the vector, which has its coordinates, you need to find the root of the square of the sum of these coordinates.

Sample tasks

Example 2

Find the distance between the points $ X $ and $ Y $, which have the following coordinates: $ (- 1.5) $ and $ (7.3) $, respectively.

Any two points can be easily associated with the concept of a vector. Consider, for example, the vector $ \\ overline (XY) $. As we already know, the coordinates of such a vector can be found by subtracting the corresponding coordinates of the starting point ($ X $) from the coordinates of the end point ($ Y $). We get that

The abscissa and ordinate axes are called coordinates vector. It is customary to indicate the coordinates of a vector in the form (x, y), and the vector itself as: \u003d (x, y).

The formula for determining the coordinates of a vector for two-dimensional problems.

In the case of a two-dimensional problem, a vector with known point coordinates A (x 1; y 1) and B (x 2 ; y 2 ) you can calculate:

\u003d (x 2 - x 1; y 2 - y 1).

The formula for determining the coordinates of a vector for spatial problems.

In the case of the spatial problem, a vector with known point coordinatesA (x 1; y 1;z 1 ) and B (x 2 ; y 2 ; z 2 ) can be calculated by applying the formula:

= (x 2 - x 1 ; y 2 - y 1 ; z 2 - z 1 ).

Coordinates give an all-encompassing characteristic of the vector, since the coordinates can be used to construct the vector itself. Knowing the coordinates, it is easy to calculate and vector length... (Property 3 below).

Vector coordinate properties.

1. Any equal vectors in a single coordinate system have equal coordinates.

2. Coordinates collinear vectors proportional. Provided that none of the vectors are zero.

3. The square of the length of any vector is equal to the sum of the squares of its coordinates.

4.During surgery vector multiplication on real number each of its coordinates is multiplied by this number.

5. When adding vectors, calculate the sum of the corresponding vector coordinates.

6. Scalar product two vectors is equal to the sum of the products of their respective coordinates.

First of all, you need to understand the very concept of a vector. In order to introduce the definition of a geometric vector, let us recall what a segment is. Let us introduce the following definition.

Definition 1

A segment is a part of a straight line that has two boundaries in the form of points.

A segment can have 2 directions. To indicate the direction, we will call one of the boundaries of the segment its beginning, and the other boundary - its end. The direction is indicated from its beginning to the end of the segment.

Definition 2

A vector or a directed segment is a segment for which it is known which of the boundaries of the segment is considered the beginning and which is its end.

Designation: Two letters: $ \\ overline (AB) $ - (where $ A $ is its beginning and $ B $ is its end).

One small letter: $ \\ overline (a) $ (fig. 1).

Let us now introduce directly the concept of vector lengths.

Definition 3

The length of the vector $ \\ overline (a) $ is the length of the segment $ a $.

Notation: $ | \\ overline (a) | $

The concept of the length of a vector is associated, for example, with such a concept as the equality of two vectors.

Definition 4

Two vectors will be called equal if they satisfy two conditions: 1. They are co-directed; 1. Their lengths are equal (Fig. 2).

In order to define vectors, a coordinate system is introduced and coordinates for the vector in the entered system are determined. As we know, any vector can be expanded as $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $, where $ m $ and $ n $ are real numbers, and $ \\ overline (i ) $ and $ \\ overline (j) $ are unit vectors on the $ Ox $ and $ Oy $ axes, respectively.

Definition 5

The expansion coefficients of the vector $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $ will be called the coordinates of this vector in the introduced coordinate system. Mathematically:

$ \\ overline (c) \u003d (m, n) $

How do I find the length of a vector?

In order to derive a formula for calculating the length of an arbitrary vector from its given coordinates, consider the following problem:

Example 1

Given: vector $ \\ overline (α) $ with coordinates $ (x, y) $. Find: the length of this vector.

Let us introduce the Cartesian coordinate system $ xOy $ on the plane. Set aside $ \\ overline (OA) \u003d \\ overline (a) $ from the origin of the introduced coordinate system. Let us construct projections $ OA_1 $ and $ OA_2 $ of the constructed vector on the axes $ Ox $ and $ Oy $, respectively (Fig. 3).

The vector $ \\ overline (OA) $ constructed by us will be the radius vector for the point $ A $, therefore, it will have coordinates $ (x, y) $, which means

$ \u003d x $, $ [OA_2] \u003d y $

Now we can easily find the required length using the Pythagorean theorem, we get

$ | \\ overline (α) | ^ 2 \u003d ^ 2 + ^ 2 $

$ | \\ overline (α) | ^ 2 \u003d x ^ 2 + y ^ 2 $

$ | \\ overline (α) | \u003d \\ sqrt (x ^ 2 + y ^ 2) $

Answer: $ \\ sqrt (x ^ 2 + y ^ 2) $.

Conclusion:To find the length of the vector, which has its coordinates, you need to find the root of the square of the sum of these coordinates.

Sample tasks

Example 2

Find the distance between the points $ X $ and $ Y $, which have the following coordinates: $ (- 1.5) $ and $ (7.3) $, respectively.

Any two points can be easily associated with the concept of a vector. Consider, for example, the vector $ \\ overline (XY) $. As we already know, the coordinates of such a vector can be found by subtracting the corresponding coordinates of the starting point ($ X $) from the coordinates of the end point ($ Y $). We get that

First of all, you need to understand the very concept of a vector. In order to introduce the definition of a geometric vector, let us recall what a segment is. Let us introduce the following definition.

Definition 1

A segment is a part of a straight line that has two boundaries in the form of points.

A segment can have 2 directions. To indicate the direction, we will call one of the boundaries of the segment its beginning, and the other boundary - its end. The direction is indicated from its beginning to the end of the segment.

Definition 2

A vector or a directed segment is a segment for which it is known which of the boundaries of the segment is considered the beginning and which is its end.

Designation: Two letters: $ \\ overline (AB) $ - (where $ A $ is its beginning and $ B $ is its end).

One small letter: $ \\ overline (a) $ (fig. 1).

Let us now introduce directly the concept of vector lengths.

Definition 3

The length of the vector $ \\ overline (a) $ is the length of the segment $ a $.

Notation: $ | \\ overline (a) | $

The concept of the length of a vector is associated, for example, with such a concept as the equality of two vectors.

Definition 4

Two vectors will be called equal if they satisfy two conditions: 1. They are co-directed; 1. Their lengths are equal (Fig. 2).

In order to define vectors, a coordinate system is introduced and coordinates for the vector in the entered system are determined. As we know, any vector can be expanded as $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $, where $ m $ and $ n $ are real numbers, and $ \\ overline (i ) $ and $ \\ overline (j) $ are unit vectors on the $ Ox $ and $ Oy $ axes, respectively.

Definition 5

The expansion coefficients of the vector $ \\ overline (c) \u003d m \\ overline (i) + n \\ overline (j) $ will be called the coordinates of this vector in the introduced coordinate system. Mathematically:

$ \\ overline (c) \u003d (m, n) $

How do I find the length of a vector?

In order to derive a formula for calculating the length of an arbitrary vector from its given coordinates, consider the following problem:

Example 1

Given: vector $ \\ overline (α) $ with coordinates $ (x, y) $. Find: the length of this vector.

Let us introduce the Cartesian coordinate system $ xOy $ on the plane. Set aside $ \\ overline (OA) \u003d \\ overline (a) $ from the origin of the introduced coordinate system. Let us construct projections $ OA_1 $ and $ OA_2 $ of the constructed vector on the axes $ Ox $ and $ Oy $, respectively (Fig. 3).

The vector $ \\ overline (OA) $ constructed by us will be the radius vector for the point $ A $, therefore, it will have coordinates $ (x, y) $, which means

$ \u003d x $, $ [OA_2] \u003d y $

Now we can easily find the required length using the Pythagorean theorem, we get

$ | \\ overline (α) | ^ 2 \u003d ^ 2 + ^ 2 $

$ | \\ overline (α) | ^ 2 \u003d x ^ 2 + y ^ 2 $

$ | \\ overline (α) | \u003d \\ sqrt (x ^ 2 + y ^ 2) $

Answer: $ \\ sqrt (x ^ 2 + y ^ 2) $.

Conclusion:To find the length of the vector, which has its coordinates, you need to find the root of the square of the sum of these coordinates.

Sample tasks

Example 2

Find the distance between the points $ X $ and $ Y $, which have the following coordinates: $ (- 1.5) $ and $ (7.3) $, respectively.

Any two points can be easily associated with the concept of a vector. Consider, for example, the vector $ \\ overline (XY) $. As we already know, the coordinates of such a vector can be found by subtracting the corresponding coordinates of the starting point ($ X $) from the coordinates of the end point ($ Y $). We get that

  • 6.4. Some applications of dot product
  • 11. Expression of the scalar product of a vector in terms of the coordinates of the factors. Theorem.
  • 12. Vector length, segment length, angle between vectors, condition of vectors perpendicularity.
  • 13. Vector product of vectors, its properties. Parallelogram area.
  • 14. Mixed product of vectors, its properties. Vector coplanarity condition. The volume of the parallelepiped. The volume of the pyramid.
  • 15. Methods for specifying a straight line on a plane.
  • 16. Normal equation of a straight line on a plane (inference). The geometric meaning of the coefficients.
  • 17. Equation of a straight line on a plane in segments (conclusion).
  • Reduction of the general equation of the plane to the equation of the plane in segments.
  • 18. Equation of a straight line on a plane with a slope (conclusion).
  • 19. Equation of a straight line on a plane passing through two points (conclusion).
  • 20. Angle between straight lines on the plane (conclusion).
  • 21. Distance from a point to a straight line on a plane (output).
  • 22. Conditions for parallelism and perpendicularity of straight lines on the plane (conclusion).
  • 23. Equation of the plane. Normal equation of the plane (inference). The geometric meaning of the coefficients.
  • 24. Equation of a plane in segments (conclusion).
  • 25. Equation of a plane passing through three points (conclusion).
  • 26. The angle between the planes (conclusion).
  • 27. Distance from point to plane (output).
  • 28. Conditions of parallelism and perpendicularity of planes (conclusion).
  • 29. Equations of a line in r3. Equations of a straight line passing through two fixed points (output).
  • 30. Canonical equations of a straight line in space (conclusion).
  • Drawing up the canonical equations of a straight line in space.
  • Particular cases of canonical equations of a line in space.
  • Canonical equations of a straight line passing through two given points in space.
  • Transition from canonical equations of a straight line in space to other types of equations of a straight line.
  • 31. The angle between straight lines (conclusion).
  • 32. Distance from a point to a straight line on a plane (output).
  • Distance from a point to a straight line on a plane - theory, examples, solutions.
  • The first way to find the distance from a given point to a given straight line on a plane.
  • The second method allows you to find the distance from a given point to a given straight line on a plane.
  • Solving problems to find the distance from a given point to a given straight line on a plane.
  • Distance from point to straight line in space - theory, examples, solutions.
  • The first way to find the distance from a point to a straight line in space.
  • The second method allows you to find the distance from a point to a straight line in space.
  • 33. Conditions for parallelism and perpendicularity of straight lines in space.
  • 34. Mutual arrangement of straight lines in space and a straight line with a plane.
  • 35. The classical equation of the ellipse (derivation) and its construction. The canonical equation of the ellipse has the form, where are positive real numbers, and. How to construct an ellipse?
  • 36. The classical equation of hyperbola (derivation) and its construction. Asymptotes.
  • 37. Canonical parabola equation (derivation) and construction.
  • 38. Function. Basic definitions. Graphs of the main elementary functions.
  • 39. Numerical sequences. Limit of a numerical sequence.
  • 40. Infinitely small and infinitely large quantities. The theorem on the connection between them, properties.
  • 41. Theorems about actions on variable quantities with finite limits.
  • 42. Number e.
  • Content
  • Determination methods
  • Properties
  • History
  • Approximations
  • 43. Determination of the limit of the function. Disclosure of uncertainties.
  • 44. Remarkable limits, their conclusion. Equivalent infinitesimal quantities.
  • Content
  • The first wonderful limit
  • Second wonderful limit
  • 45. One-sided limits. Continuity and discontinuities of a function. One-sided limits
  • Left and right function limits
  • Breakpoint of the first kind
  • Breakpoint of the second kind
  • Recoverable break point
  • 46. \u200b\u200bDefinition of the derivative. Geometric meaning, mechanical meaning of the derivative. Equations of the tangent and normal to a curve and a point.
  • 47. Theorems on the derivative of the inverse, complex functions.
  • 48. Derivatives of the simplest elementary functions.
  • 49. Differentiation of parametric, implicit and exponential functions.
  • 21. Differentiation of implicit and parametrically defined functions
  • 21.1. Implicitly specified function
  • 21.2. Parametrically defined function
  • 50. Derivatives of higher orders. Taylor's formula.
  • 51. Differential. Differential application to approximate calculations.
  • 52. Rolle's, Lagrange's, Cauchy's theorems. L'Hôpital's rule.
  • 53. Theorem about necessary and sufficient conditions for monotonicity of a function.
  • 54. Determination of the maximum, minimum of a function. Theorems about necessary and sufficient conditions for the existence of an extremum of a function.
  • Theorem (necessary condition for extremum)
  • 55. Convexity and concavity of curves. Inflection points. Theorems about necessary and sufficient conditions for the existence of inflection points.
  • Evidence
  • 57. Determinants of the n-th order, their properties.
  • 58. Matrices and actions over them. The rank of the matrix.
  • Definition
  • Related definitions
  • Properties
  • Linear transformation and matrix rank
  • 59. Inverse matrix. Existence theorem for an inverse matrix.
  • 60. Systems of linear equations. Matrix solution of systems of linear equations. Cramer's rule. Gauss method. Kronecker-Capelli theorem.
  • Solution of systems of linear algebraic equations, solution methods, examples.
  • Definitions, concepts, designations.
  • Solution of elementary systems of linear algebraic equations.
  • Solving systems of linear equations by Cramer's method.
  • Solving systems of linear algebraic equations by the matrix method (using the inverse matrix).
  • Solution of systems of linear equations by the Gauss method.
  • Solution of systems of linear algebraic equations of general form.
  • The Kronecker - Capelli theorem.
  • Gauss's method for solving systems of linear algebraic equations of general form.
  • Writing the general solution of homogeneous and inhomogeneous linear algebraic systems using vectors of the fundamental system of solutions.
  • Solution of systems of equations that reduce to slough.
  • Examples of problems that reduce to solving systems of linear algebraic equations.
  • 12. Vector length, segment length, angle between vectors, condition of vectors perpendicularity.

    Vector - it is a directional line that connects two points in space or in a plane.Vectors are usually denoted with either small letters or start and end points. A dash is usually placed on top.

    For example, a vector directed from a point A to the point B, we can denote a ,

    Zero vector 0 or 0 - it is a vector whose start and end points are the same, i.e. A = B. Hence, 0 =0 .

    Length (modulus) of a vectora is the length of the segment representing it AB, denoted by |a | ... In particular, | 0 | = 0.

    The vectors are called collinearif their directed segments lie on parallel lines. Collinear vectors a and b are designated a || b .

    Three or more vectors are called coplanarif they lie in the same plane.

    Addition of vectors. Since vectors are directed segments, then their addition can be performed geometrically. (Algebraic addition of vectors is described below, in the paragraph "Unit orthogonal vectors"). Let's pretend that

    a \u003d AB and b = CD,

    then the vector __ __

    a + b = AB+ CD

    is the result of performing two operations:

    a) parallel transfer one of the vectors so that its starting point coincides with the end point of the second vector;

    b) geometric addition, i.e. constructing the resulting vector going from the starting point of the fixed vector to the end point of the transferred vector.

    Subtraction of vectors. This operation is reduced to the previous one by replacing the subtracted vector with the opposite one: a b = a + ( b ) .

    Addition laws.

    I. a + b = b + a (Permanent law).

    II. (a + b ) + c = a + (b + c ) (Counting law).

    III. a + 0 = a .

    IV. a + ( a ) = 0 .

    The laws of multiplying a vector by a number.

    I. 1 · a = a , 0 · a = 0 , m· 0 = 0 , (1) · a = a .

    II. ma = a m, | ma | = | m | · | a | .

    III. m (na ) \u003d (m n)a . (Approx.

    law of multiplication by number).

    IV. (m + n) a = ma + na , (S d e r e l and t

    m(a + b ) = ma + mb . law of multiplication by number).

    Dot product of vectors. __ __

    Angle between nonzero vectors AB and CD - this is the angle formed by the vectors when they are parallel transferred before the points coincide A and C. Dot product of vectors a and b is called a number equal to the product of their lengths by the cosine of the angle between them:

    If one of the vectors is zero, then their dot product, in accordance with the definition, is zero:

    ( a, 0 ) = ( 0 , b ) = 0 .

    If both vectors are nonzero, then the cosine of the angle between them is calculated by the formula:

    Scalar product ( a, a ) equal to | a | 2 is called scalar square.Vector length a and its scalar square are related by the ratio:

    Dot product of two vectors:

    - positivelyif the angle between vectors acute;

    - negatively, if the angle between vectors stupid.

    The scalar product of two nonzero vectors is zero then and only if the angle between them is right, i.e. when these vectors are perpendicular (orthogonal):

    Dot product properties. For any vectors a, b, c and any number mthe following relations are valid:

    I. (a, b ) = ( b, a ) . (Permanent law)

    II. (ma, b ) = m( a, b ) .

    III.(a + b, c ) = (a, c ) + (b, c ). (Regulatory law)

    Unit orthogonal vectors. In any rectangular coordinate system, you can enter unit pairwise orthogonal vectorsi , j and k related to coordinate axes: i - with axis X, j - with axis Y and k - with axis Z... According to this definition:

    (i , j ) = (i , k ) = (j , k ) = 0,

    | i | = | j | = | k | = 1.

    Any vector a can be expressed in terms of these vectors in a unique way: a = x i + y j + z k . Another form of notation: a = (x, y, z). Here x, y, z - coordinatesvector a in this coordinate system. In accordance with the last relation and the properties of unit orthogonal vectors i, j , k the dot product of two vectors can be expressed differently.

    Let be a = (x, y, z); b = (u, v, w). Then ( a, b ) = xu + yv + zw.

    The scalar product of two vectors is equal to the sum of the products of the corresponding coordinates.

    Length (modulus) of a vector a = (x, y, z ) is equal to:

    In addition, now we get the opportunity to conduct algebraic operations on vectors, namely, addition and subtraction of vectors can be performed along the coordinates:

    a + b \u003d (x + u, y + v, z + w) ;

    a b \u003d (x u, y v, z w) .

    Vector product of vectors. Vector product [a, b ] vectorsa andb (in that order) the vector is called:

    There is another formula for the vector length [ a, b ] :

    | [ a, b ] | = | a | | b | sin ( a, b ) ,

    i.e. length ( module ) vector product of vectorsa and b is equal to the product of the lengths (modules) of these vectors by the sine of the angle between them.In other words: length (modulus) of vector[ a, b ] is numerically equal to the area of \u200b\u200ba parallelogram built on vectors a and b .

    Vector product properties.

    I.Vector [ a, b ] is perpendicular (orthogonal)both vectors a and b .

    (Prove it, please!).

    II.[ a, b ] = [ b, a ] .

    III. [ ma, b ] = m[ a, b ] .

    IV. [ a + b, c ] = [ a, c ] + [ b, c ] .

    V. [ a, [ b, c ] ] = b (a, c ) – c ( a, b ) .

    Vi. [ [ a, b ] , c ] = b (a, c ) – a (b, c ) .

    Necessary and sufficient condition for collinearity vectors a = (x, y, z) and b = (u, v, w) :

    Necessary and sufficient condition for coplanarity vectors a = (x, y, z), b = (u, v, w) and c = (p, q, r) :

    PRI me r. Given vectors: a \u003d (1, 2, 3) and b = (– 2 , 0 ,4).

    Calculate their dot and cross products and angle

    between these vectors.

    Solution. Using the corresponding formulas (see above), we get:

    a). scalar product:

    ( a, b ) \u003d 1 (- 2) + 2 0 + 3 4 \u003d 10;

    b). vector product:

    "
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