Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
3.1 Derivative of a Function lim h 0 f a h f a h We write: f is called the derivative of f x lim h 0 at a. f a h f a h “The derivative of f with respect to x is …” There are many ways to write the derivative of y f x 3.1 Derivative of a Function f x “f prime x” y “y prime” or “the derivative of f with respect to x” dy dx “dee why dee ecks” or “the derivative of y with respect to x” df dx “dee eff dee ecks” or “the derivative of f with respect to x” d f dx x “dee dee ecks uv eff uv ecks” or “the derivative ( d dx of f of x ) of f of x” 3.1 Derivative of a Function dx does not mean d times x ! dy does not mean d times y ! 3.1 Derivative of a Function dy does not mean dy dx ! dx (except when it is convenient to think of it as division.) df does not mean df dx ! dx (except when it is convenient to think of it as division.) 3.1 Derivative of a Function d d f x does not mean times f x ! dx dx (except when it is convenient to treat it that way.) 3.1 Derivative of a Function 4 3 The derivative is the slope of the original function. 2 y f x 1 0 3 1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 2 The derivative is defined at the end points of a function on a closed interval. 1 0 -1 -2 y f x 7 8 9 3.1 Derivative of a Function 6 y x 3 5 2 4 3 2 1 -3 -2 -1 0 -1 1 x 2 3 y lim -2 -3 h 0 6 5 4 3 2 1 -3 -2 -1 0 -1 -2 -3 -4 -5 -6 x h y lim 2 x h h 0 1 x 2 3 y 2 x 2 3 x2 3 h 3.1 Derivative of a Function A function is differentiable if it has a derivative everywhere in its domain. It must be continuous and smooth. Functions on closed intervals must have one-sided derivatives defined at the end points. 3.2 Differentiability To be differentiable, a function must be continuous and smooth. Derivatives will fail to exist at: f x x f x x corner f x 3 cusp f x vertical tangent 2 3 1, x 0 1, x 0 x discontinuity 3.2 Differentiability Most of the functions we study in calculus will be differentiable. 3.2 Differentiability There are two theorems on page 110: If f has a derivative at x = a, then f is continuous at x = a. Since a function must be continuous to have a derivative, if it has a derivative then it is continuous. 3.2 Differentiability Intermediate Value Theorem for Derivatives If a and b are any two points in an interval on which f is differentiable, then f takes on every value between f a and f b . 1 f a 2 f b 3 Between a and b, f must take 1 on every value between 2 and 3. 3.3 Rules for Differentiation If the derivative of a function is its slope, then for a constant function, the derivative must be zero. d c 0 dx example: y 3 y 0 The derivative of a constant is zero. 3.3 Rules for Differentiation We saw that if y x2 , y 2 x . This is part of a pattern. d n n 1 x nx dx examples: f x x f x 4x power rule y x8 4 3 y 8 x 7 3.3 Rules for Differentiation d n n 1 x nx dx Proof: d n ( x h) n x n x lim h0 dx h d n x n nx n1h ... h n x n x lim h0 dx h d n nx n1h ... hn x lim h0 dx h d n x lim nx n1 h 0 dx 3.3 Rules for Differentiation constant multiple rule: d du cu c dx dx examples: d n cx cnx n 1 dx d 7 x5 7 5 x 4 35 x 4 dx 3.3 Rules for Differentiation constant multiple rule: d du cu c dx dx sum and difference rules: d du dv u v dx dx dx d du dv u v dx dx dx 4 2 y x 2 x 2 y x 12 x (Each term is treated separately) dy 3 3 4x 4x y 4 x 12 dx 4 3.3 Rules for Differentiation Find the horizontal tangents of: y x 2x 2 4 2 dy 4 x3 4 x dx Horizontal tangents occur when slope = zero. 4 x3 4 x 0 Substituting the x values into the x3 x 0 x x 1 0 2 x x 1 x 1 0 x 0, 1, 1 original equation, we get: y 2, y 1, y 1 (The function is even, so we only get two horizontal tangents.) 3.3 Rules for Differentiation 4 y x4 2x2 2 3 -2 -1 2 y2 1 y 1 0 -1 -2 1 2 3.3 Rules for Differentiation 4 y x4 2x2 2 3 2 dy 4 x3 4 x dx 1 -2 -1 0 -1 First derivative (slope) is zero at: x 0, 1, 1 -2 1 2 3.3 Rules for Differentiation product rule: d dv du uv u v dx dx dx Notice that this is not just the product of two derivatives. This is sometimes memorized as: d uv u dv v du d 2 x 3 dx 2 x 3 x 2 3 6 x 2 5 2 x 3 5 x 2x 5x d 2 x 5 5 x 3 6 x 3 15 x dx d 2 x 5 11x 3 15 x dx 10 x 4 33 x 2 15 6 x 4 5 x 2 18 x 2 15 4 x 4 10 x 2 10 x 4 33 x 2 15 3.3 Rules for Differentiation product rule: d dv du uv u v dx dx dx d u ( x h )v ( x h ) u ( x )v ( x ) (uv) lim h0 dx h add and subtract u(x+h)v(x) in the denominator d u ( x h ) v ( x h ) u ( x )v ( x ) u ( x h )v ( x ) u ( x h )v ( x ) (uv) lim h0 dx h Proof d u ( x h)v( x h) v( x) v( x)u ( x h) u ( x) (uv) lim h 0 dx h d dv du (uv) u v dx dx dx 3.3 Rules for Differentiation quotient rule: du dv v u d u dx dx dx v v2 d 2 x 5x 2 dx x 3 3 u v du u dv d 2 v v or x 3 x 2 3 6 x 2 5 2 x3 5 x 2 x 2 2 3.3 Rules for Differentiation Higher Order Derivatives: dy y dx is the first derivative of y with respect to x. dy d dy d 2 y is the second derivative. y dx dx dx dx 2 (y double prime) dy y is the third derivative. dx We will learn later what these d 4 y y is the fourth derivative. higher order dx derivatives are used for. 3.3 Rules for Differentiation Suppose u and v are functions that are differentiable at x = 3, and that u(3) = 5, u’(3) = -7, v(3) = 1, and v’(3)= 4. Find the following at x = 3 : d 1. (uv) dx d (uv) uv' vu' dx 5(3) (1)( 7) 8 d u 2. dx v d u vu'uv' dx v v2 (1)( 7) (5)( 4) 12 27 d v 3. dx u d v uv'vu' dx u u2 (5)( 4) (1)( 7) 52 27 25 3.3 Rules for Differentiation d ho dx hi (hi)d (ho) (ho)d (hi ) (ho)( ho) 3.3 Rules for Differentiation 3.4 Velocity and other Rates of Change Consider a graph of displacement (distance traveled) vs. time. distance (miles) B A Average velocity can be found by taking: change in position s s change in time t t time (hours) Vave f t t f t s t t The speedometer in your car does not measure average velocity, but instantaneous velocity. V t f t t f t ds lim t 0 dt t (The velocity at one moment in time.) 3.4 Velocity and other Rates of Change Velocity is the first derivative of position. Acceleration is the second derivative of position. 3.4 Velocity and other Rates of Change Example: Free Fall Equation 1 2 s g t 2 s 16 t 2 1 s 32 t 2 2 ds V 32 t dt Speed is the absolute value of velocity. Gravitational Constants: ft g 32 sec 2 m g 9.8 sec 2 cm g 980 sec2 3.4 Velocity and other Rates of Change Acceleration is the derivative of velocity. dv a dt d 2s 2 dt If distance is in: example: v 32t a 32 feet Velocity would be in: feet sec Acceleration would be in: ft sec sec ft sec 2 3.4 Velocity and other Rates of Change acc neg vel pos & decreasing acc neg vel neg & decreasing acc zero vel pos & constant distance velocity zero acc pos vel pos & increasing acc zero vel neg & constant acc pos vel neg & increasing acc zero, velocity zero time 3.4 Velocity and other Rates of Change Rates of Change: f x h f x Average rate of change = h f x h f x Instantaneous rate of change = f x lim h 0 h These definitions are true for any function. ( x does not have to represent time. ) 3.4 Velocity and other Rates of Change For a circle: A r2 dA d r2 dr dr dA 2 r dr dA 2 r dr Instantaneous rate of change of the area with respect to the radius. For tree ring growth, if the change in area is constant then dr must get smaller as r gets larger. 3.4 Velocity and other Rates of Change from Economics: Marginal cost is the first derivative of the cost function, and represents an approximation of the cost of producing one more unit. 3.4 Velocity and other Rates of Change Example 13: 3 2 c x x 6 x 15x Suppose it costs: 2 to produce x stoves.c x 3x 12 x 15 If you are currently producing 10 stoves, the 11th stove will cost approximately: The actual cost is: C 11 C 10 c 10 3 102 12 10 15 300 120 15 $195 113 6 112 15 11 103 6 10 2 15 10 770 550 $220 actual cost marginal cost 3.4 Velocity and other Rates of Change Note that this is not a great approximation – Don’t let that bother you. Marginal cost is a linear approximation of a curved function. For large values it gives a good approximation of the cost of producing the next item. 3.4 Velocity and other Rates of Change 3.5 Derivatives of Trigonometric Functions Consider the function y sin We could make a graph of the slope: Now we connect the dots! The resulting curve is a cosine curve. d sin x cos x dx 2 slope 1 0 0 2 1 1 0 3.5 Derivatives of Trigonometric Functions Proof d sin( x h) sin x sin x lim h0 dx h d sin x cos h sin h cos x sin x sin x lim h0 dx h d sin x (cos h 1) sin h cos x sin x lim h0 dx h d sin x (cos h 1) sin h cos x sin x lim lim h0 h0 dx h h 3.5 Derivatives of Trigonometric Functions =0 =1 d sin x (cos h 1) sin h cos x sin x lim lim h0 h0 dx h h d sin x cos x dx 3.5 Derivatives of Trigonometric Functions Find the derivative of cos x d cos( x h) cos x cos x lim h0 dx h d cos x cos h sin h sin x cos x cos x lim h0 dx h d cos x (cos h 1) sin h sin x cos x lim h0 dx h d cos x (cos h 1) sin h sin x cos x lim lim h0 h0 dx h h 3.5 Derivatives of Trigonometric Functions =0 =1 d cos x (cos h 1) sin h sin x cos x lim lim h0 h0 dx h h d cos x sin x dx 3.5 Derivatives of Trigonometric Functions We can find the derivative of tangent x by using the quotient rule. d tan x dx cos 2 x sin 2 x cos 2 x d sin x dx cos x 1 cos 2 x cos x cos x sin x sin x cos 2 x d tan x sec 2 x dx sec 2 x 3.5 Derivatives of Trigonometric Functions Derivatives of the remaining trig functions can be determined the same way. d sin x cos x dx d cot x csc 2 x dx d cos x sin x dx d sec x sec x tan x dx d tan x sec 2 x dx d csc x csc x cot x dx 3.5 Derivatives of Trigonometric Functions Jerk A sudden change in acceleration Definition Jerk Jerk is the derivative of acceleration. If a body’s position at time t is s(t), the body’s jerk at time t is da d 2v d 3s j (t ) 2 3 dt dt dt 3.5 Derivatives of Trigonometric Functions 3.6 Chain Rule Consider a simple composite function: y 6 x 10 y 2 3x 5 If u 3x 5 then y 2u y 6 x 10 y 2u dy 6 dx dy 2 du 6 23 dy dy du dx du dx u 3x 5 du 3 dx 3.6 Chain Rule Chain Rule: dy dy du dx du dx If f g is the composite of y f u and u g x , then: f g fat u g x gat x f ' ( g ( x)) g ' ( x) example: f g at x 2 f x sin x g x x2 4 f x cos x g x 2x g 2 4 4 0 cos 0 2 2 1 4 f 0 g 2 Find: 4 3.6 Chain Rule f g x sin x 2 4 y sin x 2 4 y sin u u x2 4 dy cos u du du 2x dx dy dy du dx du dx dy cos u 2 x dx dy cos x 2 4 2 x dx dy cos 22 4 2 2 dx dy cos 0 4 dx dy 4 dx 3.6 Chain Rule Here is a faster way to find the derivative: y sin x 2 4 d 2 y cos x 4 x 4 dx 2 y cos x 2 4 2 x At x 2, y 4 Differentiate the outside function... …then the inside function 3.6 Chain Rule d cos 2 3 x dx d 2 cos 3x cos 3x dx d 2 cos 3x sin 3 x 3 x dx 2cos 3x sin 3x 3 6cos 3x sin 3x 2 d cos 3 x dx The chain rule can be used more than once. (That’s what makes the “chain” in the “chain rule”!) 3.6 Chain Rule Derivative formulas include the chain rule! d n n 1 du u nu dx dx d du sin u cos u dx dx d du cos u sin u dx dx d du 2 tan u sec u dx dx etcetera… 3.6 Chain Rule Find dy dx y cos(3x 2 x) dy sin( 3x 2 x)(6 x 1) dx y sin(cos( x)) dy cos(cos x)( sin x) dx dy 3 cos 2 (4 x3 2 x)( sin( 4 x3 2 x))(12 x 2 2) dx dy (36 x 2 6) cos 2 (4 x3 2 x)( sin( 4 x3 2 x)) dx y cos3 (4 x3 2 x) 3.6 Chain Rule The chain rule enables us to find the slope of parametrically defined curves: dy dy dx dt dx dt dy dt dy dx dx dt The slope of a parametrized curve is given by: dy dy dt dx dx dt 3.6 Chain Rule Example: These are the equations for an ellipse. x 3cos t dx dy 3sin t 2 cos t dt dt y 2sin t dy 2 cos t 2 cot t dx 3sin t 3 3.7 Implicit Differentiation x2 y 2 1 d 2 d 2 d x y 1 dx dx dx dy 2x 2 y 0 dx dy 2y 2 x dx This is not a function, but it would still be nice to be able to find the slope. Do the same thing to both sides. Note use of chain rule. dy 2 x dx 2 y dy x dx y 3.7 Implicit Differentiation This can’t be solved for y. 2 y x 2 sin y d d 2 d dy 2x 2y x sin y dx dx dx dx 2 cos y dy dy 2 2 x cos y This technique is called dx dx implicit differentiation. dy dy 2 cos y 2x dx dx 1 Differentiate both sides w.r.t. x. dy dy 2 cos y 2 x 2 Solve for . dx dx 3.7 Implicit Differentiation Implicit Differentiation Process 1. 2. 3. 4. Differentiate both sides of the equation with respect to x. Collect the terms with dy/dx on one side of the equation. Factor out dy/dx . Solve for dy/dx . 3.7 Implicit Differentiation Find the equations of the lines tangent and normal to the curve x 2 xy y 2 7 at (1, 2) . x 2 xy y 2 7 Note product rule. dy dy 2x x y 2 y 0 dx dx dy dy 2x x y 2 y 0 dx dx dy 2 y x y 2x dx dy y 2 x dx 2 y x 2 2 1 22 4 m 2 2 1 4 1 5 3.7 Implicit Differentiation Find the equations of the lines tangent and normal to the curve 4 m 5 x 2 xy y 2 7 at (1, 2) . tangent: normal: 4 y 2 x 1 5 4 4 y2 x 5 5 5 y 2 x 1 4 5 5 y2 x 4 4 4 14 y x 5 5 5 3 y x 4 4 3.7 Implicit Differentiation 3.7 Implicit Differentiation d2y 3 2 Find if 2 x 3 y 7 . 2 dx y 2 x x 2 y y 3 2 2x 3 y 7 y2 6 x 6 y y 0 2 6 y y 6 x 2 6 x 2 y 6 y x2 y y 2x x 2 y 2 y y y 2x x 2 x 2 y 2 y y y 2x x 4 y 3 y y Substitute y back into the equation. 3.7 Implicit Differentiation Rational Powers of Differentiable Functions Power Rule for Rational Powers of x If n is any rational number, then d n x nx n1 dx 3.7 Implicit Differentiation Proof: Let p and q be integers with q > 0. yx p q yq x p qy q 1 Raise both sides to the q power Differentiate with respect to x dy p 1 px dx Solve for dy/dx 3.7 Implicit Differentiation dy px p1 q1 dx qy Substitute for y dy px p1 p / q q 1 dx q( x ) p 1 dy px p p / q dx qx dy px p1( p p / q ) dx q Remove parenthesis Subtract exponents dy p ( p / q )1 x dx q 3.8 Derivatives of Inverse Trigonometric Functions y 8 Slopes are reciprocals. y x2 Because x and y are reversed to find the reciprocal function, the following pattern always holds: 6 4 2, 4 2 m4 4, 2 0 0 2 y 1 m 4 4 6 x 8 The derivative of f 1 ( x) x Derivative Formula for Inverses: 1 df dx x f (a) 1 df dx x a evaluated at f ( a ) is equal to the reciprocal of the derivative of f ( x ) evaluated at a . 3.8 Derivatives of Inverse Trigonometric Functions We can use implicit differentiation to find: d sin 1 x dx 1.5 y sin 1 x 1 y sin x 0.5 y sin 1 x -1.5 -1 -0.5 0 -0.5 sin y x dy cos y 1 dx d d sin y x dx dx dy 1 dx cos y -1 -1.5 0.5 1 1.5 3.8 Derivatives of Inverse Trigonometric Functions We can use implicit differentiation to find: y sin 1 x sin y x dy cos y 1 dx dy 1 dx cos y d sin 1 x dx sin 2 y cos2 y 1 d d sin y x dx dx cos2 y 1 sin 2 y dy 1 dx 1 sin 2 y dy 1 dx 1 x2 cos y 1 sin 2 y But y 2 2 so cos y is positive. cos y 1 sin 2 y 3.8 Derivatives of Inverse Trigonometric Functions y sin 1 x sin y x dy cos y 1 dx dy 1 dx cos y dy 1 dx cos(sin 1 x) dy 1 dx 1 x2 1 x sin 1 x 1 x2 3.8 Derivatives of Inverse Trigonometric Functions d 1 tan x Find dx y tan 1 x tan y x dy sec y 1 dx 2 dy 1 dx sec 2 y dy 1 dx sec 2 (tan 1 x) 1 x2 x 1 dy 1 dx 1 x 2 tan x 1 3.8 Derivatives of Inverse Trigonometric Functions d 1 sec x Find dx y sec 1 x sec y x dy 1 dx sec(sec 1 x) tan(sec 1 x) dy 1 dy sec y tan y 1 dx | x | x 2 1 dx dy 1 dx sec y tan y x x2 1 sec 1 x 1 3.8 Derivatives of Inverse Trigonometric Functions 1 cos x 2 1 1 sin x cot x d 1 du sin 1 u dx 1 u 2 dx d 1 du tan 1 u dx 1 u 2 dx d 1 du 1 sec u dx u u 2 1 dx 2 1 1 tan x csc x 2 sec 1 x d 1 du cos 1 u dx 1 u 2 dx d 1 du 1 cot u dx 1 u 2 dx d 1 du 1 csc u dx u u 2 1 dx 3.8 Derivatives of Inverse Trigonometric Functions Your calculator contains all six inverse trig functions. However it is occasionally still useful to know the following: 1 sec x cos x 1 1 cot x 1 2 1 tan x 1 csc x sin x 1 1 3.8 Derivatives of Inverse Trigonometric Functions Find dy dx 1 y cos (3x ) 2 1 y cot x 1 y x sec1 x dy 1 6x (6 x ) 2 2 dx (1 (3x ) 1 9 x4 dy 1 1 1 2 2 1 x x 1 dx 1 2 x dy 1 x (sec 1 x)(1) dx | x | x2 1 3.9 Derivatives of Exponential and Logarithmic Functions Look at the graph of ye x 3 2 The slope at x = 0 appears to be 1. If we assume this to be true, then: 1 lim e h 0 -3 -2 -1 0 -1 1 x 2 0 h e 1 h 0 3 definition of derivative 3.9 Derivatives of Exponential and Logarithmic Functions Now we attempt to find a general formula for the x derivative of y e using the definition. d x e xh e x e lim h 0 dx h e x eh e x lim h 0 h x eh 1 lim e h 0 h h e 1 x e lim h 0 h This is the slope at x = 0, which we have assumed to be 1. e 1 x e x d x x e e dx 3.9 Derivatives of Exponential and Logarithmic Functions e x is its own derivative! If we incorporate the chain rule: d u u du e e dx dx We can now use this formula to find the derivative of ax 3.9 Derivatives of Exponential and Logarithmic Functions d x a dx d ln a x e dx d x ln a e dx d x ln a e x ln a dx d x x a a ln a dx Incorporating the chain rule: d u du u a a ln a dx dx 3.9 Derivatives of Exponential and Logarithmic Functions So far today we have: d u u du e e dx dx d du u u a a ln a dx dx Now it is relatively easy to find the derivative of ln x . 3.9 Derivatives of Exponential and Logarithmic Functions y ln x y e x d y d e x dx dx y dy e 1 dx dy 1 y dx e d 1 ln x dx x d 1 du ln u dx u dx 3.9 Derivatives of Exponential and Logarithmic Functions To find the derivative of a common log function, you could just use the change of base rule for logs: d d ln x 1 d 1 1 log x ln x dx dx ln10 ln10 dx ln10 x The formula for the derivative of a log of any base other than e is: d 1 du log a u dx u ln a dx 3.9 Derivatives of Exponential and Logarithmic Functions d u u du e e dx dx d du u u a a ln a dx dx d 1 du ln u dx u dx d 1 du log a u dx u ln a dx 3.9 Derivatives of Exponential and Logarithmic Functions Find y’ ye y 3 2x 2x y' 2e x2 y' 3 ln( 3)(2 x) 1 3 2 y ' 3 (3x ) x x 1 4x y' (e )( 4) 4x 2 1 (e ) x2 y ln x 3 1 y sin (e ) 4x 3.9 Derivatives of Exponential and Logarithmic Functions Logarithmic differentiation Used when the variable is in the base and the exponent y = xx ln y = ln xx ln y = x ln x 1 dy 1 x ln x y dx x dy y 1 ln x dx dy x x 1 ln x dx