There's an obvious guess for the rule about the derivative of a product—which happens to be wrong. We explain the correct product rule and why it has to be true, along with the quotient rule. We show how to compute derivatives of additional trigonometric functions and new proofs of the Power Rule.
Lesson 9: The Product and Quotient Rules (slides)Matthew Leingang
The product rule is generally better because:
- It is more systematic and avoids mistakes from expanding products
- It works for any differentiable functions u and v, not just polynomials
- It provides insight into the structure of the derivative that direct computation does not
So in this example, using the product rule is preferable to direct multiplication.
This document provides an overview of engineering mathematics II with a focus on first order ordinary differential equations (ODEs). It explains what first order ODEs are, how to solve separable and reducible first order ODEs, and provides examples of applying first order ODEs to model real-world scenarios like population growth, decay, and radioactive decay. The objectives are to explain first order ODEs, separable equations, and apply the concepts to real life applications.
This document provides an introduction to partial differentiation, including:
- Defining partial derivatives and how they are calculated by treating all but one variable as a constant
- Examples of finding partial derivatives using the product, quotient, and chain rules
- Higher order partial derivatives and mixed partial derivatives
- Notation for partial derivatives
- A quiz on partial derivatives concepts
This document provides solutions to 14 exercises involving solving first order homogeneous and non-homogeneous differential equations. The solutions involve identifying whether the equations are homogeneous, making substitutions to reduce non-homogeneous equations to homogeneous form, finding integrating factors, and integrating to obtain the general solutions. Key steps include denoting y=vx to make equations homogeneous, solving for constants to determine substitutions, and manipulating integrals to isolate the dependent variables.
The document provides a brief refresher on key concepts in calculus, including:
1) The basic rules of differentiation like the power rule, constant rule, sum and difference rule, product rule, and quotient rule.
2) The chain rule for finding derivatives of composite functions.
3) Higher-order derivatives and notation for second and third derivatives.
4) Concepts of absolute extrema and critical points for finding the maximum and minimum values of functions.
The document provides examples demonstrating the chain rule for differentiating composite functions. The chain rule states that if y = g(u) and u = f(x), then dy/dx = (dy/du) * (du/dx). Several examples are worked through applying the chain rule to functions composed of multiple operations like sin(x^2) or (x^2 + 5x - 1)^(2/3). The chain rule can be extended to chains of more than two functions as shown in later examples.
There's an obvious guess for the rule about the derivative of a product—which happens to be wrong. We explain the correct product rule and why it has to be true, along with the quotient rule. We show how to compute derivatives of additional trigonometric functions and new proofs of the Power Rule.
Lesson 9: The Product and Quotient Rules (slides)Matthew Leingang
The product rule is generally better because:
- It is more systematic and avoids mistakes from expanding products
- It works for any differentiable functions u and v, not just polynomials
- It provides insight into the structure of the derivative that direct computation does not
So in this example, using the product rule is preferable to direct multiplication.
This document provides an overview of engineering mathematics II with a focus on first order ordinary differential equations (ODEs). It explains what first order ODEs are, how to solve separable and reducible first order ODEs, and provides examples of applying first order ODEs to model real-world scenarios like population growth, decay, and radioactive decay. The objectives are to explain first order ODEs, separable equations, and apply the concepts to real life applications.
This document provides an introduction to partial differentiation, including:
- Defining partial derivatives and how they are calculated by treating all but one variable as a constant
- Examples of finding partial derivatives using the product, quotient, and chain rules
- Higher order partial derivatives and mixed partial derivatives
- Notation for partial derivatives
- A quiz on partial derivatives concepts
This document provides solutions to 14 exercises involving solving first order homogeneous and non-homogeneous differential equations. The solutions involve identifying whether the equations are homogeneous, making substitutions to reduce non-homogeneous equations to homogeneous form, finding integrating factors, and integrating to obtain the general solutions. Key steps include denoting y=vx to make equations homogeneous, solving for constants to determine substitutions, and manipulating integrals to isolate the dependent variables.
The document provides a brief refresher on key concepts in calculus, including:
1) The basic rules of differentiation like the power rule, constant rule, sum and difference rule, product rule, and quotient rule.
2) The chain rule for finding derivatives of composite functions.
3) Higher-order derivatives and notation for second and third derivatives.
4) Concepts of absolute extrema and critical points for finding the maximum and minimum values of functions.
The document provides examples demonstrating the chain rule for differentiating composite functions. The chain rule states that if y = g(u) and u = f(x), then dy/dx = (dy/du) * (du/dx). Several examples are worked through applying the chain rule to functions composed of multiple operations like sin(x^2) or (x^2 + 5x - 1)^(2/3). The chain rule can be extended to chains of more than two functions as shown in later examples.
The document is a lesson on implicit differentiation and related concepts:
1) Implicit differentiation allows one to take the derivative of an implicitly defined relation between x and y, even if y is not explicitly defined as a function of x.
2) Examples are provided to demonstrate implicit differentiation, such as finding the slope of a tangent line to a curve.
3) The van der Waals equation is introduced to describe non-ideal gas properties, and implicit differentiation is used to find the isothermal compressibility of a van der Waals gas.
Lesson 27: Integration by Substitution (Section 4 version)Matthew Leingang
The document outlines a calculus lecture on integration by substitution. It provides examples of using u-substitution to find antiderivatives of expressions like √(x^2+1) and tan(x). The key ideas are that if u is a function of x, its derivative du/dx can be used to rewrite the integrand and perform a u-substitution integration.
Lesson 27: Integration by Substitution (Section 10 version)Matthew Leingang
The method of substitution is the chain rule in reverse. At first it looks magical, then logical, and then you realize there's an art to choosing the right substitution. We try to demystify with many worked-out examples.
1. The document discusses transformation of random variables, where a function g is applied to a random variable X to produce another random variable Y=g(X). It provides methods to find the density or distribution function of Y based on the density of X.
2. It examines two examples that use the distribution function method and density function method to find the density of Y when X has a standard normal distribution and Y is a transformation of X.
3. It introduces the Jacobian technique to generalize the density function method to problems with multiple inputs and outputs. The Jacobian allows transforming joint densities between different variable spaces using a determinant.
The document explains the chain rule, which provides a method for finding the derivative of a composite function. The chain rule states that the derivative of a composite function f(g(x)) is equal to the derivative of the outside function f'(g(x)) multiplied by the derivative of the inside function g'(x). This allows the calculation of derivatives of more complex functions that cannot be solved using basic derivative rules. Several examples are provided to demonstrate how to use the chain rule to calculate derivatives of various composite functions.
Integration by substitution is the chain rule in reverse.
NOTE: the final location is section specific. Section 1 (morning) is in SILV 703, Section 11 (afternoon) is in CANT 200
This document discusses the derivation of a Quotient Rule Integration by Parts formula. It shows how the student Victor Reynolds asked if a similar formula could be derived from the Quotient Rule as the standard Integration by Parts formula is derived from the Product Rule. The author proceeds to derive such a Quotient Rule Integration by Parts formula. An example application of the new formula is also shown. However, the formula does not appear in calculus texts because it provides only a slight technical advantage over the standard formula and requires the same integral computations.
The document discusses error propagation in physics measurements and calculations. It provides formulas for calculating the uncertainty (error) when adding, subtracting, multiplying and dividing measurements. The key points are:
1) When adding or subtracting measurements, the total uncertainty is the square root of the sum of the individual measurement uncertainties squared.
2) When multiplying or dividing measurements, the total uncertainty is calculated by adding the individual relative uncertainties squared.
3) For measurements raised to a power, the relative uncertainty is equal to the relative uncertainty of the measurement itself multiplied by the power.
Lesson 27: Integration by Substitution, part II (Section 10 version)Matthew Leingang
The document is the notes for a Calculus I class. It provides announcements for the upcoming class on Monday, which will involve reviewing course material rather than new topics. Examples are given of integration by substitution, including exponential, odd, and even functions. Multiple methods for substitutions are presented. The properties of odd and even functions are defined, and examples are shown graphically. Symmetric functions and their behavior under combinations are discussed.
Solving second order ordinary differential equations (boundary value problems) using the Least Squares Technique. Contains one numerical examples from Shah, Eldho, Desai
The document discusses velocity and acceleration in terms of position x. It provides equations showing that acceleration is equal to the derivative of velocity with respect to time, and the derivative of velocity with respect to x. It also gives examples of using these relationships to find velocity and position as functions of x and time for particles where acceleration is given.
The chain rule helps us find a derivative of a composition of functions. It turns out that it's the product of the derivatives of the composed functions.
Lesson03 Dot Product And Matrix Multiplication Slides NotesMatthew Leingang
The document discusses the dot product and matrix multiplication. It defines the dot product of two vectors p and q as the sum of the element-wise products of corresponding entries. The dot product is a scalar. Matrix-vector multiplication is defined as taking the dot product of each row of the matrix with the vector to produce another vector, with the dimensions working out properly. An example calculates the matrix-vector product of a given matrix and vector.
This document discusses solving second-order linear differential equations near a regular singular point, which is done by assuming power series solutions and obtaining recursion relations between the coefficients. Specifically, it provides an example of solving the differential equation ( ) 012 2=++′−′′ yxyxyx near the regular singular point x=0. Two linearly independent solutions are obtained in the forms of ( )( )∑∞=1!12753)1( nnnxaxy and ( )( )∑∞=12/1!12531)1( nnnxaxy , yielding the general solution ( )0),()()( 2211 >+= xxycxycxy .
The document is a lesson on continuity and infinite limits. It defines infinite limits, including limits approaching positive or negative infinity. It provides examples of evaluating limits at points where a function is not continuous. It also outlines several rules of thumb for manipulating infinite limits, such as the sum or product of an infinite limit with a finite limit being infinite. The document cautions that limits of indeterminate forms like 0×∞ or ∞-∞ require closer examination rather than following rules of thumb. It provides an example of rationalizing an expression to put it in a form where limit laws can be applied.
This document discusses continuity and the Intermediate Value Theorem (IVT) in mathematics. It defines continuity, examines examples of continuous and discontinuous functions, and establishes theorems about continuity. The IVT states that if a function is continuous on a closed interval and takes on intermediate values within its range, there exists at least one value in the domain where the function value is intermediate. An example proves the existence of the square root of two using the IVT and bisection method.
This document discusses continuity and the Intermediate Value Theorem (IVT) in mathematics. It defines continuity, examines examples of continuous and discontinuous functions, and describes special types of discontinuities. The IVT states that if a function is continuous on a closed interval and takes on intermediate values, there exists a number in the interval where the function value is equal to the intermediate value. Examples are provided to illustrate the IVT, including proving the existence of the square root of two.
Lesson 18: Geometric Representations of FunctionsMatthew Leingang
This document provides an outline for a lesson on geometric representations of functions of several variables. It includes examples of graphing linear functions, paraboloids, hyperbolic paraboloids, and Cobb-Douglas functions. It also discusses contour plots, intersecting cones to get circles, and indifference curves as level curves of utility functions where all points have the same utility value.
The document is a lesson on implicit differentiation and related concepts:
1) Implicit differentiation allows one to take the derivative of an implicitly defined relation between x and y, even if y is not explicitly defined as a function of x.
2) Examples are provided to demonstrate implicit differentiation, such as finding the slope of a tangent line to a curve.
3) The van der Waals equation is introduced to describe non-ideal gas properties, and implicit differentiation is used to find the isothermal compressibility of a van der Waals gas.
Lesson 27: Integration by Substitution (Section 4 version)Matthew Leingang
The document outlines a calculus lecture on integration by substitution. It provides examples of using u-substitution to find antiderivatives of expressions like √(x^2+1) and tan(x). The key ideas are that if u is a function of x, its derivative du/dx can be used to rewrite the integrand and perform a u-substitution integration.
Lesson 27: Integration by Substitution (Section 10 version)Matthew Leingang
The method of substitution is the chain rule in reverse. At first it looks magical, then logical, and then you realize there's an art to choosing the right substitution. We try to demystify with many worked-out examples.
1. The document discusses transformation of random variables, where a function g is applied to a random variable X to produce another random variable Y=g(X). It provides methods to find the density or distribution function of Y based on the density of X.
2. It examines two examples that use the distribution function method and density function method to find the density of Y when X has a standard normal distribution and Y is a transformation of X.
3. It introduces the Jacobian technique to generalize the density function method to problems with multiple inputs and outputs. The Jacobian allows transforming joint densities between different variable spaces using a determinant.
The document explains the chain rule, which provides a method for finding the derivative of a composite function. The chain rule states that the derivative of a composite function f(g(x)) is equal to the derivative of the outside function f'(g(x)) multiplied by the derivative of the inside function g'(x). This allows the calculation of derivatives of more complex functions that cannot be solved using basic derivative rules. Several examples are provided to demonstrate how to use the chain rule to calculate derivatives of various composite functions.
Integration by substitution is the chain rule in reverse.
NOTE: the final location is section specific. Section 1 (morning) is in SILV 703, Section 11 (afternoon) is in CANT 200
This document discusses the derivation of a Quotient Rule Integration by Parts formula. It shows how the student Victor Reynolds asked if a similar formula could be derived from the Quotient Rule as the standard Integration by Parts formula is derived from the Product Rule. The author proceeds to derive such a Quotient Rule Integration by Parts formula. An example application of the new formula is also shown. However, the formula does not appear in calculus texts because it provides only a slight technical advantage over the standard formula and requires the same integral computations.
The document discusses error propagation in physics measurements and calculations. It provides formulas for calculating the uncertainty (error) when adding, subtracting, multiplying and dividing measurements. The key points are:
1) When adding or subtracting measurements, the total uncertainty is the square root of the sum of the individual measurement uncertainties squared.
2) When multiplying or dividing measurements, the total uncertainty is calculated by adding the individual relative uncertainties squared.
3) For measurements raised to a power, the relative uncertainty is equal to the relative uncertainty of the measurement itself multiplied by the power.
Lesson 27: Integration by Substitution, part II (Section 10 version)Matthew Leingang
The document is the notes for a Calculus I class. It provides announcements for the upcoming class on Monday, which will involve reviewing course material rather than new topics. Examples are given of integration by substitution, including exponential, odd, and even functions. Multiple methods for substitutions are presented. The properties of odd and even functions are defined, and examples are shown graphically. Symmetric functions and their behavior under combinations are discussed.
Solving second order ordinary differential equations (boundary value problems) using the Least Squares Technique. Contains one numerical examples from Shah, Eldho, Desai
The document discusses velocity and acceleration in terms of position x. It provides equations showing that acceleration is equal to the derivative of velocity with respect to time, and the derivative of velocity with respect to x. It also gives examples of using these relationships to find velocity and position as functions of x and time for particles where acceleration is given.
The chain rule helps us find a derivative of a composition of functions. It turns out that it's the product of the derivatives of the composed functions.
Lesson03 Dot Product And Matrix Multiplication Slides NotesMatthew Leingang
The document discusses the dot product and matrix multiplication. It defines the dot product of two vectors p and q as the sum of the element-wise products of corresponding entries. The dot product is a scalar. Matrix-vector multiplication is defined as taking the dot product of each row of the matrix with the vector to produce another vector, with the dimensions working out properly. An example calculates the matrix-vector product of a given matrix and vector.
This document discusses solving second-order linear differential equations near a regular singular point, which is done by assuming power series solutions and obtaining recursion relations between the coefficients. Specifically, it provides an example of solving the differential equation ( ) 012 2=++′−′′ yxyxyx near the regular singular point x=0. Two linearly independent solutions are obtained in the forms of ( )( )∑∞=1!12753)1( nnnxaxy and ( )( )∑∞=12/1!12531)1( nnnxaxy , yielding the general solution ( )0),()()( 2211 >+= xxycxycxy .
The document is a lesson on continuity and infinite limits. It defines infinite limits, including limits approaching positive or negative infinity. It provides examples of evaluating limits at points where a function is not continuous. It also outlines several rules of thumb for manipulating infinite limits, such as the sum or product of an infinite limit with a finite limit being infinite. The document cautions that limits of indeterminate forms like 0×∞ or ∞-∞ require closer examination rather than following rules of thumb. It provides an example of rationalizing an expression to put it in a form where limit laws can be applied.
This document discusses continuity and the Intermediate Value Theorem (IVT) in mathematics. It defines continuity, examines examples of continuous and discontinuous functions, and establishes theorems about continuity. The IVT states that if a function is continuous on a closed interval and takes on intermediate values within its range, there exists at least one value in the domain where the function value is intermediate. An example proves the existence of the square root of two using the IVT and bisection method.
This document discusses continuity and the Intermediate Value Theorem (IVT) in mathematics. It defines continuity, examines examples of continuous and discontinuous functions, and describes special types of discontinuities. The IVT states that if a function is continuous on a closed interval and takes on intermediate values, there exists a number in the interval where the function value is equal to the intermediate value. Examples are provided to illustrate the IVT, including proving the existence of the square root of two.
Lesson 18: Geometric Representations of FunctionsMatthew Leingang
This document provides an outline for a lesson on geometric representations of functions of several variables. It includes examples of graphing linear functions, paraboloids, hyperbolic paraboloids, and Cobb-Douglas functions. It also discusses contour plots, intersecting cones to get circles, and indifference curves as level curves of utility functions where all points have the same utility value.
This document contains notes for a lesson on the chain rule from a Calculus 1 class. It defines the chain rule formula and provides an example of applying the chain rule to find the derivative of a function. It also includes another example problem and its step-by-step solution using the chain rule. The document concludes with a metaphor to help understand applying the chain rule.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document discusses continuity and the Intermediate Value Theorem (IVT) in mathematics. It defines continuity, examines examples of continuous and discontinuous functions, and establishes theorems about continuity. The IVT states that if a function is continuous on a closed interval and takes on intermediate values within its range, there exists at least one value in the domain where the function value is intermediate. An example proves the existence of the square root of two using the IVT and bisection method.
This document summarizes a lesson on the spectral theorem and its applications:
1) It introduces the spectral theorem, which states that certain matrices can be diagonalized, such as symmetric matrices.
2) It shows how the spectral theorem can be used to derive an explicit formula for the Fibonacci sequence by representing it as a matrix equation and diagonalizing the matrix.
3) It discusses how the spectral theorem can be applied to analyze Markov chains through diagonalization of the transition matrix.
The document is a 17 page math document titled "Math 1a - October 24, 2007.GWB" that was created on Wednesday, October 24, 2007 and contains content spanning multiple pages.
This document contains lecture notes from a Math 1a class on October 17, 2007. It discusses increasing and decreasing functions, and concavity and the second derivative. It provides definitions of increasing, decreasing, concave up, and concave down functions on an interval based on the sign of the function. It also lists several facts, such as if a function is increasing on an interval then it is greater than or equal to 0 on that interval.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document summarizes a lesson on diagonalization of matrices. It defines eigenvalues and eigenvectors, provides an example to illustrate the geometric effect of a non-diagonal linear transformation, and outlines the procedure for diagonalizing a matrix by finding its eigenvalues and eigenvectors and arranging them into diagonal and invertible matrices. It also gives an worked example of diagonalizing a specific 2x2 matrix.
The document discusses functions of several variables. It provides examples of multivariable functions including temperature in a room being a function of position and time, and economic production being a function of capital and labor. It then outlines topics to be covered, such as linear functions, polynomials, and finding domains of multivariable functions. An example problem is given of expressing the profit, flour needed, and sugar needed to make x rolls and y cookies.
The document discusses related rates problems in mathematics. It provides examples of how to solve related rates problems using derivatives and the chain rule. In one example, the radius of an oil slick is increasing and the volume is known to be increasing at a rate of 10,000 liters per second. The problem is to determine the rate of change of the radius. The solution uses derivatives and the geometry of the situation to set up and solve an equation relating the rates of change. A second example involves determining the rate at which two people walking away from each other are increasing their distance apart.
Lesson14: Derivatives of Trigonometric FunctionsMatthew Leingang
This document contains notes from a calculus class that discusses:
1) Two important limits involving trigonometric functions - the limit of sin(θ)/θ as θ approaches 0 equals 1, and the limit of (cos(θ) - 1)/θ as θ approaches 0 equals 0.
2) The derivatives of sine and cosine - the derivative of sine is cosine, and the derivative of cosine is the negative of sine.
3) The derivative of tangent is secant squared, and the derivative of secant is secant times tangent.
This document contains multiple definitions and examples related to limits at infinity:
1) It defines limits at infinity and horizontal asymptotes, stating that a limit equals a value L if the function values can be made arbitrarily close to L by taking x sufficiently large or small.
2) Examples show computing limits by factoring out highest degree terms and applying limits laws, such as a limit equaling 1/2.
3) Additional examples provide strategies for determining limits at infinity, such as comparing exponential to geometric growth rates or rationalizing nondeterminate forms.
Lesson 13: Rank and Solutions to Systems of Linear EquationsMatthew Leingang
This document provides an overview of lesson 12 on rank and solutions to systems of linear equations. It defines rank as the maximum number of linearly independent column vectors in a matrix and discusses how to compute rank using Gaussian elimination and minors. It also relates rank to the consistency and redundancy of systems of linear equations, noting that a system is consistent if the rank of the coefficient matrix equals the rank of the augmented matrix, and redundant or free variables exist if the ranks are less than the number of equations or variables respectively.
The document is notes for a lesson on partial derivatives. It introduces partial derivatives and their motivation as slopes of curves through a point on a multi-variable function. It defines partial derivatives mathematically and gives an example. It also discusses second partial derivatives and notes that mixed partials are always equal due to Clairaut's Theorem when the function is continuous. Finally, it provides an example of calculating second partial derivatives.
The product rule can be iterated to find the derivative of products with more than two factors. The derivative of a three-factor product uvw is u'vw + uv'w + uvw'. More generally, the derivative of a product of n factors breaks the product into a sum of n terms by applying the product rule recursively.
1. The document discusses solving trigonometric equations and finding their general solutions. It provides examples of solving equations using inverse trig functions, factoring, and substitution.
2. General solutions to trig equations involve adding integer multiples of the period (2π or 180°) to the solutions to account for all possibilities in the entire domain.
3. Examples show solving equations like cosx = 0.456 by taking the inverse cosine and factoring equations like 3tan^2x + 4tanx + 1 = 0 to find specific solutions and the general form.
The document introduces linear programming through an example of a candy manufacturer that must determine how many cases of two candy products to make to maximize profit given constraints on available ingredients. It defines variables and constraints, graphs the feasible region, determines the optimal solution that maximizes profit, and discusses how linear programming can be applied to problems with multiple variables and constraints.
1. The document discusses algebraic principles for multiplying and factorizing sums and differences of numbers. It introduces the formula (a + b)(c + d) = ac + ad + bc + bd for multiplying two sums, and similar formulas for multiplying sums and differences.
2. It then applies these formulas to derive algebraic identities for the square of a sum, the difference of squares, and the product of a sum and difference. Examples are provided to demonstrate how these identities can be used to simplify calculations.
3. Readers are prompted with examples to practice applying the different algebraic formulas and identities introduced in the document.
Basic differential equations in fluid mechanicsTarun Gehlot
This document provides an overview of fluid dynamics concepts including the continuity equation, Navier-Stokes equations, and examples of their application to laminar flow situations. It derives the 1-dimensional continuity equation and uses it to describe flow between parallel plates. It then derives the equation for laminar flow velocity profile between infinite horizontal parallel plates based on the Navier-Stokes equations and applies it to calculate discharge rate. Finally, it provides an example problem calculating discharge rate and power for an oil skimming device.
The document provides an overview of constrained optimization using Lagrange multipliers. It begins with motivational examples of constrained optimization problems and then introduces the method of Lagrange multipliers, which involves setting up equations involving the functions to optimize and constrain and a Lagrange multiplier. Examples are worked through to demonstrate solving these systems of equations to find critical points. Caution is advised about dividing equations where one side could be zero. A contour plot example visually depicts the constrained critical points.
1) Implicit differentiation is a method for finding the slope of a curve when the equation is given implicitly rather than explicitly as y = f(x).
2) Examples are given of implicitly defined curves like circles, ellipses, and a 4-leaf clover curve.
3) The process of implicit differentiation takes the derivative of both sides of the implicit equation and solves for the derivative dy/dx.
In this presentation we solve two more examples of implicit differentiation problems. We use a faster, more direct method.
For more lessons visit: http://www.intuitive-calculus.com/implicit-differentiation.html
Using implicit differentiation we can treat relations which are not quite functions like they were functions. In particular, we can find the slopes of lines tangent to curves which are not graphs of functions.
Using implicit differentiation we can treat relations which are not quite functions like they were functions. In particular, we can find the slopes of lines tangent to curves which are not graphs of functions.
The document discusses implicit differentiation, which allows one to find the derivative of functions defined by a relation rather than explicitly. It gives an example of implicitly differentiating the relation x^2 + y^2 = 25 using the chain rule. Applying implicit differentiation and the chain rule derives the solution y = -x/y, which verifies the original implicit definition of the function.
This document presents several theorems related to establishing the existence and uniqueness of a common fixed point for nonlinear contractive mappings in Hilbert spaces. It begins by introducing the background and motivation for studying fixed point theory and various generalizations of the Banach contraction principle. It then lists several existing theorems that establish fixed point results for mappings satisfying different contraction conditions in complete metric and Hilbert spaces. The main part of the document presents new fixed point theorems for continuous self-mappings on closed subsets of a Hilbert space, proving the existence and uniqueness of a fixed point when the mappings satisfy certain rational-type contraction conditions.
This document provides examples and explanations of transformations of trigonometric functions including phase shifts and vertical/horizontal shifts. It discusses how to write alternative equations for shifted trig functions by following patterns of + and - signs. Examples are provided comparing graphs of original and transformed trig functions to illustrate various shifts. The document also discusses concepts of phase relationships between voltage and current in AC circuits including being in phase, out of phase, and maximum inductance occurring when voltage leads current by a phase of π/2 radians. Homework problems from p. 282 #1-20 are assigned.
Here are the key steps:
1) Choose u and dv based on LIPET:
u = ex
dv = cos x dx
2) Find du and v:
du = ex dx
v = sin x
3) Apply integration by parts formula:
∫uex dx = uv - ∫vdu
= exsinx - ∫sinxexdx
4) Repeat integration by parts on the second term:
∫sinxexdx = excosx - ∫-cosxexdx
5) Combine like terms:
exsinx + excosx - ∫excosxdx
6) The integral on the right is
This document contains lecture notes on calculus including:
- Announcements about upcoming quizzes and exams
- An outline of topics to be covered including the derivative of a product, quotient rule, and power rule
- Examples of solving continuity problems using theorems
- A discussion of the derivative of a product of functions and how it is not simply the product of the individual derivatives
- Examples worked out step-by-step for understanding the concepts
Proofs Methods and Strategy
CMSC 56 | Discrete Mathematical Structure for Computer Science
September 10, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
Trigonometric substitutions can help evaluate integrals involving trigonometric functions. The document provides examples of using trigonometric substitutions to evaluate integrals of powers of sine and cosine functions. Specifically:
1) Integrals of powers of sine and cosine can be evaluated by rewriting the functions using trigonometric identities and then substituting variables. For example, sin5x can be rewritten as sinx(sin2x)2 and evaluated using the substitution u=cosx.
2) More complex integrals may require multiple steps and identities. For example, evaluating sin6x requires rewriting sin2x using an identity and then integrating four resulting terms.
3) Trigonometric substitutions allow rewriting integrals involving
The document discusses the binomial theorem, which describes the pattern that emerges when a binomial is multiplied by itself multiple times. Specifically:
- When a binomial of the form (a + b) is raised to a power n, the terms follow the pattern an-kbk, where k goes from 0 to n.
- The coefficients of these terms form Pascal's triangle, where each number is the sum of the two above it.
- This allows one to expand complex expressions like (a + b)4 as a4 + 4a3b + 6a2b2 + 4ab3 + b4.
The binomial theorem thus provides a formulaic way to determine the terms and
Similar to Lesson 12: The Product and Quotient Rule (20)
This document provides guidance on developing effective lesson plans for calculus instructors. It recommends starting by defining specific learning objectives and assessments. Examples should be chosen carefully to illustrate concepts and engage students at a variety of levels. The lesson plan should include an introductory problem, definitions, theorems, examples, and group work. Timing for each section should be estimated. After teaching, the lesson can be improved by analyzing what was effective and what needs adjustment for the next time. Advanced preparation is key to looking prepared and ensuring students learn.
Streamlining assessment, feedback, and archival with auto-multiple-choiceMatthew Leingang
Auto-multiple-choice (AMC) is an open-source optical mark recognition software package built with Perl, LaTeX, XML, and sqlite. I use it for all my in-class quizzes and exams. Unique papers are created for each student, fixed-response items are scored automatically, and free-response problems, after manual scoring, have marks recorded in the same process. In the first part of the talk I will discuss AMC’s many features and why I feel it’s ideal for a mathematics course. My contributions to the AMC workflow include some scripts designed to automate the process of returning scored papers
back to students electronically. AMC provides an email gateway, but I have written programs to return graded papers via the DAV protocol to student’s dropboxes on our (Sakai) learning management systems. I will also show how graded papers can be archived, with appropriate metadata tags, into an Evernote notebook.
This document discusses electronic grading of paper assessments using PDF forms. Key points include:
- Various tools for creating fillable PDF forms using LaTeX packages or desktop software.
- Methods for stamping completed forms onto scanned documents including using pdftk or overlaying in TikZ.
- Options for grading on tablets or desktops including GoodReader, PDFExpert, Adobe Acrobat.
- Extracting data from completed forms can be done in Adobe Acrobat or via command line with pdftk.
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
g(x) represents the area under the curve of f(t) between 0 and x.
.
x
What can you say about g? 2 4 6 8 10f
The First Fundamental Theorem of Calculus
Theorem (First Fundamental Theorem of Calculus)
Let f be a con nuous func on on [a, b]. Define the func on F on [a, b] by
∫ x
F(x) = f(t) dt
a
Then F is con nuous on [a, b] and differentiable on (a, b) and for all x in (a, b),
F′(x
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
The document discusses the Fundamental Theorem of Calculus, which has two parts. The first part states that if a function f is continuous on an interval, then the derivative of the integral of f is equal to f. This is proven using Riemann sums. The second part relates the integral of a function f to the integral of its derivative F'. Examples are provided to illustrate how the area under a curve relates to these concepts.
Lesson 27: Integration by Substitution (handout)Matthew Leingang
This document contains lecture notes on integration by substitution from a Calculus I class. It introduces the technique of substitution for both indefinite and definite integrals. For indefinite integrals, the substitution rule is presented, along with examples of using substitutions to evaluate integrals involving polynomials, trigonometric, exponential, and other functions. For definite integrals, the substitution rule is extended and examples are worked through both with and without first finding the indefinite integral. The document emphasizes that substitution often simplifies integrals and makes them easier to evaluate.
Lesson 26: The Fundamental Theorem of Calculus (handout)Matthew Leingang
1) The document discusses lecture notes on Section 5.4: The Fundamental Theorem of Calculus from a Calculus I course. 2) It covers stating and explaining the Fundamental Theorems of Calculus and using the first fundamental theorem to find derivatives of functions defined by integrals. 3) The lecture outlines the first fundamental theorem, which relates differentiation and integration, and gives examples of applying it.
This document contains notes from a calculus class lecture on evaluating definite integrals. It discusses using the evaluation theorem to evaluate definite integrals, writing derivatives as indefinite integrals, and interpreting definite integrals as the net change of a function over an interval. The document also contains examples of evaluating definite integrals, properties of integrals, and an outline of the key topics covered.
This document contains lecture notes from a Calculus I class covering Section 5.3 on evaluating definite integrals. The notes discuss using the Evaluation Theorem to calculate definite integrals, writing derivatives as indefinite integrals, and interpreting definite integrals as the net change of a function over an interval. Examples are provided to demonstrate evaluating definite integrals using the midpoint rule approximation. Properties of integrals such as additivity and the relationship between definite and indefinite integrals are also outlined.
Lesson 24: Areas and Distances, The Definite Integral (handout)Matthew Leingang
We can define the area of a curved region by a process similar to that by which we determined the slope of a curve: approximation by what we know and a limit.
Lesson 24: Areas and Distances, The Definite Integral (slides)Matthew Leingang
We can define the area of a curved region by a process similar to that by which we determined the slope of a curve: approximation by what we know and a limit.
At times it is useful to consider a function whose derivative is a given function. We look at the general idea of reversing the differentiation process and its applications to rectilinear motion.
At times it is useful to consider a function whose derivative is a given function. We look at the general idea of reversing the differentiation process and its applications to rectilinear motion.
This document contains lecture notes from a Calculus I class discussing optimization problems. It begins with announcements about upcoming exams and courses the professor is teaching. It then presents an example problem about finding the rectangle of a fixed perimeter with the maximum area. The solution uses calculus techniques like taking the derivative to find the critical points and determine that the optimal rectangle is a square. The notes discuss strategies for solving optimization problems and summarize the key steps to take.
Uncountably many problems in life and nature can be expressed in terms of an optimization principle. We look at the process and find a few good examples.
The document discusses curve sketching of functions by analyzing their derivatives. It provides:
1) A checklist for graphing a function which involves finding where the function is positive/negative/zero, its monotonicity from the first derivative, and concavity from the second derivative.
2) An example of graphing the cubic function f(x) = 2x^3 - 3x^2 - 12x through analyzing its derivatives.
3) Explanations of the increasing/decreasing test and concavity test to determine monotonicity and concavity from a function's derivatives.
The document contains lecture notes on curve sketching from a Calculus I class. It discusses using the first and second derivative tests to determine properties of a function like monotonicity, concavity, maxima, minima, and points of inflection in order to sketch the graph of the function. It then provides an example of using these tests to sketch the graph of the cubic function f(x) = 2x^3 - 3x^2 - 12x.
Lesson 20: Derivatives and the Shapes of Curves (slides)Matthew Leingang
This document contains lecture notes on derivatives and the shapes of curves from a Calculus I class taught by Professor Matthew Leingang at New York University. The notes cover using derivatives to determine the intervals where a function is increasing or decreasing, classifying critical points as maxima or minima, using the second derivative to determine concavity, and applying the first and second derivative tests. Examples are provided to illustrate finding intervals of monotonicity for various functions.
Lesson 20: Derivatives and the Shapes of Curves (handout)Matthew Leingang
This document contains lecture notes on calculus from a Calculus I course. It covers determining the monotonicity of functions using the first derivative test. Key points include using the sign of the derivative to determine if a function is increasing or decreasing over an interval, and using the first derivative test to classify critical points as local maxima, minima, or neither. Examples are provided to demonstrate finding intervals of monotonicity for various functions and applying the first derivative test.
The Mean Value Theorem is the most important theorem in calculus. It is the first theorem which allows us to infer information about a function from information about its derivative. From the MVT we can derive tests for the monotonicity (increase or decrease) and concavity of a function.
4. Is the derivative of a product the product of the
derivatives?
NO!
Try this with u = x and v = x 2 .
5. Is the derivative of a product the product of the
derivatives?
NO!
Try this with u = x and v = x 2 . Then uv = x 3 , so (uv ) = 3x 2 .
But u v = 1(2x) = 2x.
6. Is the derivative of a product the product of the
derivatives?
NO!
Try this with u = x and v = x 2 . Then uv = x 3 , so (uv ) = 3x 2 .
But u v = 1(2x) = 2x.
So we have to be more careful.
7. Mmm...burgers
Say you work in a fast-food joint. You want to make more money.
What are your choices?
8. Mmm...burgers
Say you work in a fast-food joint. You want to make more money.
What are your choices?
Work longer hours.
9. Mmm...burgers
Say you work in a fast-food joint. You want to make more money.
What are your choices?
Work longer hours.
Get a raise.
10. Mmm...burgers
Say you work in a fast-food joint. You want to make more money.
What are your choices?
Work longer hours.
Get a raise.
Say you get a 25 cent raise in your hourly wages and work 5 hours
more per week. How much extra money do you make?
11. Money money money money
The answer depends on how much you work already and your
current wage. Suppose you work h hours and are paid w . You get
a time increase of ∆h and a wage increase of ∆w . Income is
wages times hours, so
∆I = (w + ∆w )(h + ∆h) − wh
FOIL
= wh + w ∆h + ∆w h + ∆w ∆h − wh
= w ∆h + ∆w h + ∆w ∆h
13. A geometric argument
Draw a box:
∆h w ∆h ∆w ∆h
h wh ∆w h
w ∆w
∆I = w ∆h + h ∆w + ∆w ∆h
14. Supose wages and hours are changing over time. How does income
change?
∆I w ∆h + h ∆w + ∆w ∆h
=
∆t ∆t
∆h ∆w ∆h
=w +h + ∆w
∆t ∆t ∆t
dh dw
→w +h +0
dt dt
as t → 0.
15.
16. Supose wages and hours are changing over time. How does income
change?
∆I w ∆h + h ∆w + ∆w ∆h
=
∆t ∆t
∆h ∆w ∆h
=w +h + ∆w
∆t ∆t ∆t
dh dw
→w +h +0
dt dt
as t → 0.
Theorem (The Product Rule)
Let u and v be differentiable at x. Then
(uv ) (x) = u(x)v (x) + u (x)v (x)
23. The Quotient Rule
What about the derivative of a quotient?
u
Let u and v be differentiable and let Q = . Then u = Qv . If Q
v
is differentiable, we have
u = (Qv ) = Q v + Qv
u − Qv u uv
Q = = − 2
v v v
u v − uv
=
v2
24. The Quotient Rule
What about the derivative of a quotient?
u
Let u and v be differentiable and let Q = . Then u = Qv . If Q
v
is differentiable, we have
u = (Qv ) = Q v + Qv
u − Qv u uv
Q = = − 2
v v v
u v − uv
=
v2
This is called the Quotient Rule.
25. Examples
Example
d 2x + 5
1.
dx 3x − 2
d 2x + 1
2.
dx x 2 − 1
d t −1
3. 2+t +2
.
dt t
26. Examples
Example
d 2x + 5
1.
dx 3x − 2
d 2x + 1
2.
dx x 2 − 1
d t −1
3. 2+t +2
.
dt t
Answers
27. Examples
Example
d 2x + 5
1.
dx 3x − 2
d 2x + 1
2.
dx x 2 − 1
d t −1
3. 2+t +2
.
dt t
Answers
19
1. −
(3x − 2)2
28. Examples
Example
d 2x + 5
1.
dx 3x − 2
d 2x + 1
2.
dx x 2 − 1
d t −1
3. 2+t +2
.
dt t
Answers
19
1. −
(3x − 2)2
2 x2 + x + 1
2. −
(x 2 − 1)2
29. Examples
Example
d 2x + 5
1.
dx 3x − 2
d 2x + 1
2.
dx x 2 − 1
d t −1
3. 2+t +2
.
dt t
Answers
19
1. −
(3x − 2)2
2 x2 + x + 1
2. −
(x 2 − 1)2
−t 2 + 2t + 3
3.
(t 2 + t + 2)2
30. Example (Quadratic Tangent to identity function)
The curve y = ax 2 + bx + c passes through the point (1, 2) and is
tangent to the line y = x at the point (0, 0). Find a, b, and c.
31. Example (Quadratic Tangent to identity function)
The curve y = ax 2 + bx + c passes through the point (1, 2) and is
tangent to the line y = x at the point (0, 0). Find a, b, and c.
Answer
a = 1, b = 1, c = 0.
32. Power Rule for nonnegative integers by induction
Theorem
Let n be a positive integer. Then
d n
x = nx n−1 .
dx
33. Power Rule for nonnegative integers by induction
Theorem
Let n be a positive integer. Then
d n
x = nx n−1 .
dx
Proof.
By induction on n. We have shown it to be true for n = 1.
d n
Suppose for some n that x = nx n−1 . Then
dx
d n+1 d
x = (x · x n )
dx dx
d d n
= x xn + x x
dx dx
= 1 · x n + x · nx n−1 = (n + 1)x n .
34. Power Rule for negative integers
Use the quotient rule to prove
Theorem
d −n
x = (−n)x −n−1 .
dx
for positive integers n.
35. Power Rule for negative integers
Use the quotient rule to prove
Theorem
d −n
x = (−n)x −n−1 .
dx
for positive integers n.
Proof.
d −n d 1
x =
dx dx x n
d d
x n dx 1 − 1 dx x n
=
x 2n
0 − nx n−1
= = −nx −n−1 .
x 2n