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κ = ‖ T ′ ( t ) ‖ ‖ r ′ ( t ) ‖ or κ = ‖ r ′ ( t ) × r ″ ( t ) ‖ ‖ r ′ ( t ) ‖ 3 or κ = | y ″ | [ 1 + ( y ′ ) 2 ] 3 / 2 κ = ‖ T ′ ( t ) ‖ ‖ r ′ ( t ) ‖ or κ = ‖ r ′ ( t ) × r ″ ( t ) ‖ ‖ r ′ ( t ) ‖ 3 or κ = | y ″ | [ 1 + ( y ′ ) 2 ] 3 / 2
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
N ( t ) = T ′ ( t ) ‖ T ′ ( t ) ‖ N ( t ) = T ′ ( t ) ‖ T ′ ( t ) ‖
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
B ( t ) = T ( t ) × N ( t ) B ( t ) = T ( t ) × N ( t )
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
v ( t ) = r ′ ( t ) v ( t ) = r ′ ( t )
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
a ( t ) = v ′ ( t ) = r″ ( t ) a ( t ) = v ′ ( t ) = r″ ( t )
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
v ( t ) = ‖ v ( t ) ‖ = ‖ r ′ ( t ) ‖ = d s d t v ( t ) = ‖ v ( t ) ‖ = ‖ r ′ ( t ) ‖ = d s d t
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
a T = a · T = v · a ‖ v ‖ a T = a · T = v · a ‖ v ‖
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
a N = a · N = ‖ v × a ‖ ‖ v ‖ = ‖ a ‖ 2 − a T 2 a N = a · N = ‖ v × a ‖ ‖ v ‖ = ‖ a ‖ 2 − a T 2
https://openstax.org/books/calculus-volume-3/pages/3-key-equations
acceleration vector : the second derivative of the position vector
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
arc-length function : a functions(t)s(t)that describes the arc length of curveCas a function oft
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
arc-length parameterization : a reparameterization of a vector-valued function in which the parameter is equal to the arc length
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
binormal vector : a unit vector orthogonal to the unit tangent vector and the unit normal vector
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component functions : the component functions of the vector-valued functionr(t)=f(t)i+g(t)jr(t)=f(t)i+g(t)jaref(t)f(t)andg(t),g(t),and the component functions of the vector-valued functionr(t)=f(t)i+g(t)j+h(t)kr(t)=f(t)i+g(t)j+h(t)karef(t),f(t),g(t)g(t)andh(t)h(t)
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
curvature : the derivative of the unit tangent vector with respect to the arc-length parameter
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definite integral of a vector-valued function : the vector obtained by calculating the definite integral of each of the component functions of a given vector-valued function, then using the results as the components of the resulting function
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
derivative of a vector-valued function : the derivative of a vector-valued functionr(t)r(t)isr′(t)=limΔt→0r(t+Δt)−r(t)Δt,r′(t)=limΔt→0r(t+Δt)−r(t)Δt,provided the limit exists
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
Frenet frame of reference : (TNB frame) a frame of reference in three-dimensional space formed by the unit tangent vector, the unit normal vector, and the binormal vector
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
helix : a three-dimensional curve in the shape of a spiral
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
indefinite integral of a vector-valued function : a vector-valued function with a derivative that is equal to a given vector-valued function
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
Kepler’s laws of planetary motion : three laws governing the motion of planets, asteroids, and comets in orbit around the Sun
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
limit of a vector-valued function : a vector-valued functionr(t)r(t)has a limitLastapproachesaiflimt→a|r(t)−L|=0limt→a|r(t)−L|=0
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
normal component of acceleration : the coefficient of the unit normal vectorNwhen the acceleration vector is written as a linear combination ofTTandNN
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
normal plane : a plane that is perpendicular to a curve at any point on the curve
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osculating circle : a circle that is tangent to a curveCat a pointPand that shares the same curvature
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osculating plane : the plane determined by the unit tangent and the unit normal vector
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plane curve : the set of ordered pairs(f(t),g(t))(f(t),g(t))together with their defining parametric equationsx=f(t)x=f(t)andy=g(t)y=g(t)
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principal unit normal vector : a vector orthogonal to the unit tangent vector, given by the formulaT′(t)‖T′(t)‖T′(t)‖T′(t)‖
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
principal unit tangent vector : a unit vector tangent to a curveC
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
projectile motion : motion of an object with an initial velocity but no force acting on it other than gravity
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
radius of curvature : the reciprocal of the curvature
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reparameterization : an alternative parameterization of a given vector-valued function
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smooth : curves where the vector-valued functionr(t)r(t)is differentiable with a non-zero derivative
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space curve : the set of ordered triples(f(t),g(t),h(t))(f(t),g(t),h(t))together with their defining parametric equationsx=f(t),x=f(t),y=g(t)y=g(t)andz=h(t)z=h(t)
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tangent vector : tor(t)r(t)att=t0t=t0any vectorvsuch that, when the tail of the vector is placed at pointr(t0)r(t0)on the graph, vectorvis tangent to curveC
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tangential component of acceleration : the coefficient of the unit tangent vectorTwhen the acceleration vector is written as a linear combination ofTTandNN
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vector parameterization : any representation of a plane or space curve using a vector-valued function
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vector-valued function : a function of the formr(t)=f(t)i+g(t)jr(t)=f(t)i+g(t)jorr(t)=f(t)i+g(t)j+h(t)k,r(t)=f(t)i+g(t)j+h(t)k,where the component functionsf, g,andhare real-valued functions of the parametert
https://openstax.org/books/calculus-volume-3/pages/3-key-terms
velocity vector : the derivative of the position vector
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The graph of a function of two variables is a surface inℝ3ℝ3and can be studied using level curves and vertical traces.
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
A set of level curves is called a contour map.
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To study limits and continuity for functions of two variables, we use aδδdisk centered around a given point.
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A function of several variables has a limit if for any point in aδδball centered at a pointP,P,the value of the function at that point is arbitrarily close to a fixed value (the limit value).
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
The limit laws established for a function of one variable have natural extensions to functions of more than one variable.
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A function of two variables is continuous at a point if the limit exists at that point, the function exists at that point, and the limit and function are equal at that point.
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
A partial derivative is a derivative involving a function of more than one independent variable.
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To calculate a partial derivative with respect to a given variable, treat all the other variables as constants and use the usual differentiation rules.
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Higher-order partial derivatives can be calculated in the same way as higher-order derivatives.
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
The analog of a tangent line to a curve is a tangent plane to a surface for functions of two variables.
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Tangent planes can be used to approximate values of functions near known values.
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
A function is differentiable at a point if it is ”smooth” at that point (i.e., no corners or discontinuities exist at that point).
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The total differential can be used to approximate the change in a functionz=f(x0,y0)z=f(x0,y0)at the point(x0,y0)(x0,y0)for given values ofΔxΔxandΔy.Δy.
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The chain rule for functions of more than one variable involves the partial derivatives with respect to all the independent variables.
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Tree diagrams are useful for deriving formulas for the chain rule for functions of more than one variable, where each independent variable also depends on other variables.
https://openstax.org/books/calculus-volume-3/pages/4-key-concepts
A directional derivative represents a rate of change of a function in any given direction.
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The gradient can be used in a formula to calculate the directional derivative.
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The gradient indicates the direction of greatest change of a function of more than one variable.
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A critical point of the functionf(x,y)f(x,y)is any point(x0,y0)(x0,y0)where eitherfx(x0,y0)=fy(x0,y0)=0,fx(x0,y0)=fy(x0,y0)=0,or at least one offx(x0,y0)fx(x0,y0)andfy(x0,y0)fy(x0,y0)do not exist.
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A saddle point is a point(x0,y0)(x0,y0)wherefx(x0,y0)=fy(x0,y0)=0,fx(x0,y0)=fy(x0,y0)=0,but(x0,y0)(x0,y0)is neither a maximum nor a minimum at that point.
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To find extrema of functions of two variables, first find the critical points, then calculate the discriminant and apply the second derivative test.
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An objective function combined with one or more constraints is an example of an optimization problem.
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To solve optimization problems, we apply the method of Lagrange multipliers using a four-step problem-solving strategy.
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f ( a , y ) = z f ( a , y ) = z for x = a x = a or f ( x , b ) = z f ( x , b ) = z for y = b y = b
https://openstax.org/books/calculus-volume-3/pages/4-key-equations
f ( x , y , z ) = c f ( x , y , z ) = c
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∂ f ∂ x = lim h → 0 f ( x + h , y ) − f ( x , y ) h ∂ f ∂ x = lim h → 0 f ( x + h , y ) − f ( x , y ) h
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∂ f ∂ y = lim k → 0 f ( x , y + k ) − f ( x , y ) k ∂ f ∂ y = lim k → 0 f ( x , y + k ) − f ( x , y ) k
https://openstax.org/books/calculus-volume-3/pages/4-key-equations
z = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) z = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 )
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L ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) L ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 )
https://openstax.org/books/calculus-volume-3/pages/4-key-equations
d z = f x ( x 0 , y 0 ) d x + f y ( x 0 , y 0 ) d y . d z = f x ( x 0 , y 0 ) d x + f y ( x 0 , y 0 ) d y .
https://openstax.org/books/calculus-volume-3/pages/4-key-equations
f ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) + E ( x , y ) , f ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) + E ( x , y ) , where the error term E E satisfies lim ( x , y ) → ( x 0 , y 0 ) E ( x , y ) ( x − x 0 )...
https://openstax.org/books/calculus-volume-3/pages/4-key-equations
f ( x , y ) = f ( x 0 , y 0 , z 0 ) + f x ( x 0 , y 0 , z 0 ) ( x − x 0 ) + f y ( x 0 , y 0 , z 0 ) ( y − y 0 ) + f z ( x 0 , y 0 , z 0 ) ( z − z 0 ) + E ( x , y , z ) , f ( x , y ) = f ( x 0 , y 0 , z 0 ) + f x ( x 0 , y 0 , z 0 ) ( x − x 0 ) + f y ( x 0 , y 0 , z 0 ) ( y − y 0 ) + f z ( x 0 , y 0 , z 0 ) ( ...
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d z d t = ∂ z ∂ x · d x d t + ∂ z ∂ y · d y d t d z d t = ∂ z ∂ x · d x d t + ∂ z ∂ y · d y d t
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d z d u = ∂ z ∂ x ∂ x ∂ u + ∂ z ∂ y ∂ x ∂ u d z d u = ∂ z ∂ x ∂ x ∂ u + ∂ z ∂ y ∂ x ∂ u d z d v = ∂ z ∂ x ∂ x ∂ v + ∂ z ∂ y ∂ y ∂ v d z d v = ∂ z ∂ x ∂ x ∂ v + ∂ z ∂ y ∂ y ∂ v
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∂ w ∂ t j = ∂ w ∂ x 1 ∂ x 1 ∂ t j + ∂ w ∂ x 2 ∂ x 1 ∂ t j + ⋯ + ∂ w ∂ x m ∂ x m ∂ t j ∂ w ∂ t j = ∂ w ∂ x 1 ∂ x 1 ∂ t j + ∂ w ∂ x 2 ∂ x 1 ∂ t j + ⋯ + ∂ w ∂ x m ∂ x m ∂ t j
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D u f ( a , b ) = lim h → 0 f ( a + h cos θ , b + h sin θ ) − f ( a , b ) h D u f ( a , b ) = lim h → 0 f ( a + h cos θ , b + h sin θ ) − f ( a , b ) h or D u f ( x , y ) = f x ( x , y ) cos θ + f y ( x , y ) sin θ D u f ( x , y ) = f x ( x , y ) cos θ + f y ( x , y ) sin θ
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∇ f ( x , y ) = f x ( x , y ) i + f y ( x , y ) j ∇ f ( x , y ) = f x ( x , y ) i + f y ( x , y ) j
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∇ f ( x , y , z ) = f x ( x , y , z ) i + f y ( x , y , z ) j + f z ( x , y , z ) k ∇ f ( x , y , z ) = f x ( x , y , z ) i + f y ( x , y , z ) j + f z ( x , y , z ) k
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D u f ( x , y , z ) = ∇ f ( x , y , z ) · u = f x ( x , y , z ) cos α + f y ( x , y , z ) cos β + f x ( x , y , z ) cos γ D u f ( x , y , z ) = ∇ f ( x , y , z ) · u = f x ( x , y , z ) cos α + f y ( x , y , z ) cos β + f x ( x , y , z ) cos γ
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D = f x x ( x 0 , y 0 ) f y y ( x 0 , y 0 ) − ( f x y ( x 0 , y 0 ) ) 2 D = f x x ( x 0 , y 0 ) f y y ( x 0 , y 0 ) − ( f x y ( x 0 , y 0 ) ) 2
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∇ f ( x 0 , y 0 ) = λ ∇ g ( x 0 , y 0 ) g ( x 0 , y 0 ) = 0 ∇ f ( x 0 , y 0 ) = λ ∇ g ( x 0 , y 0 ) g ( x 0 , y 0 ) = 0
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∇ f ( x 0 , y 0 , z 0 ) = λ 1 ∇ g ( x 0 , y 0 , z 0 ) + λ 2 ∇ h ( x 0 , y 0 , z 0 ) g ( x 0 , y 0 , z 0 ) = 0 h ( x 0 , y 0 , z 0 ) = 0 ∇ f ( x 0 , y 0 , z 0 ) = λ 1 ∇ g ( x 0 , y 0 , z 0 ) + λ 2 ∇ h ( x 0 , y 0 , z 0 ) g ( x 0 , y 0 , z 0 ) = 0 h ( x 0 , y 0 , z 0 ) = 0
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boundary point : a pointP0P0ofRRis a boundary point if everyδδdisk centered aroundP0P0contains points both inside and outsideRR
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closed set : a setSSthat contains all its boundary points
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connected set : an open setSSthat cannot be represented as the union of two or more disjoint, nonempty open subsets
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constraint : an inequality or equation involving one or more variables that is used in an optimization problem; the constraint enforces a limit on the possible solutions for the problem
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contour map : a plot of the various level curves of a given functionf(x,y)f(x,y)
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critical point of a function of two variables : the point(x0,y0)(x0,y0)is called a critical point off(x,y)f(x,y)if one of the two following conditions holds:fx(x0,y0)=fy(x0,y0)=0fx(x0,y0)=fy(x0,y0)=0At least one offx(x0,y0)fx(x0,y0)andfy(x0,y0)fy(x0,y0)do not exist
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differentiable : a functionf(x,y,z)f(x,y,z)is differentiable at(x0,y0)(x0,y0)iff(x,y)f(x,y)can be expressed in the formf(x,y)=f(x0,y0)+fx(x0,y0)(x−x0)+fy(x0,y0)(y−y0)+E(x,y),f(x,y)=f(x0,y0)+fx(x0,y0)(x−x0)+fy(x0,y0)(y−y0)+E(x,y),where the error termE(x,y)E(x,y)satisfieslim(x,y)→(x0,y0)E(x,y)(x−x0)2+(y−y0)...
https://openstax.org/books/calculus-volume-3/pages/4-key-terms
directional derivative : the derivative of a function in the direction of a given unit vector
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discriminant : the discriminant of the functionf(x,y)f(x,y)is given by the formulaD=fxx(x0,y0)fyy(x0,y0)−(fxy(x0,y0))2D=fxx(x0,y0)fyy(x0,y0)−(fxy(x0,y0))2
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function of two variables : a functionz=f(x,y)z=f(x,y)that maps each ordered pair(x,y)(x,y)in a subsetDDofℝ2ℝ2to a unique real numberzz
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generalized chain rule : the chain rule extended to functions of more than one independent variable, in which each independent variable may depend on one or more other variables
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gradient : the gradient of the functionf(x,y)f(x,y)is defined to be∇f(x,y)=(∂f/∂x)i+(∂f/∂y)j,∇f(x,y)=(∂f/∂x)i+(∂f/∂y)j,which can be generalized to a function of any number of independent variables
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graph of a function of two variables : a set of ordered triples(x,y,z)(x,y,z)that satisfies the equationz=f(x,y)z=f(x,y)plotted in three-dimensional Cartesian space
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higher-order partial derivatives : second-order or higher partial derivatives, regardless of whether they are mixed partial derivatives
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interior point : a pointP0P0ofRRis a boundary point if there is aδδdisk centered aroundP0P0contained completely inRR
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intermediate variable : given a composition of functions (e.g.,f(x(t),y(t))),f(x(t),y(t))),the intermediate variables are the variables that are independent in the outer function but dependent on other variables as well; in the functionf(x(t),y(t)),f(x(t),y(t)),the variablesxandyxandyare examples of intermediate variab...
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Lagrange multiplier : the constant (or constants) used in the method of Lagrange multipliers; in the case of one constant, it is represented by the variableλλ
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level curve of a function of two variables : the set of points satisfying the equationf(x,y)=cf(x,y)=cfor some real numberccin the range offf
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level surface of a function of three variables : the set of points satisfying the equationf(x,y,z)=cf(x,y,z)=cfor some real numberccin the range offf
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linear approximation : given a functionf(x,y)f(x,y)and a tangent plane to the function at a point(x0,y0),(x0,y0),we can approximatef(x,y)f(x,y)for points near(x0,y0)(x0,y0)using the tangent plane formula
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