The document provides an outline and definitions for sections 3.1 and 3.2 of a calculus class, which cover exponential and logarithmic functions. It defines exponential functions, establishes conventions for exponents of all types, and graphs exponential functions. Key points covered include the properties of exponential functions and defining exponents for non-whole number bases.
This document provides an overview of exponential functions including:
- Definitions of exponential functions for positive integer, rational, and irrational exponents. Conventions are established to define exponents for all real number bases and exponents.
- Properties of exponential functions including that they are continuous functions with domain of all real numbers and range from 0 to infinity. Properties involving addition, subtraction, multiplication, and division of exponents are proven.
- Examples are provided to demonstrate simplifying expressions using properties of exponents, including fractional exponents.
Lesson 13: Exponential and Logarithmic Functions (slides)Matthew Leingang
The document provides an outline and definitions for sections 3.1 and 3.2 of a calculus class, which cover exponential and logarithmic functions. It defines exponential functions, establishes conventions for exponents of all types, and graphs exponential functions. Key points covered include the properties of exponential functions and defining exponents for non-whole number bases.
Exponential functions change addition into multiplication. Different bases for exponentials produce different functions but they share similar characteristics. One base--a number we call e--is an especially good one.
Exponential functions change addition into multiplication. Different bases for exponentials produce different functions but they share similar characteristics. One base--a number we call e--is an especially good one.
Ian.petrow【transcendental number theory】.Tong Leung
This document provides an introduction and overview of the course "Math 249A Fall 2010: Transcendental Number Theory" taught by Kannan Soundararajan. It discusses topics that will be covered, including proving that specific numbers like e, π, and combinations of them are transcendental. Theorems are presented on approximating algebraic numbers and showing linear independence of exponential functions of algebraic numbers. Examples are given of using an integral technique to derive contradictions and prove transcendence.
The document introduces the integral test, which can be used to determine if an infinite series is convergent or divergent. The integral test states that a series is convergent if the corresponding improper integral converges, and divergent if the improper integral diverges. Several examples demonstrate applying the integral test to various series by setting up and evaluating the corresponding improper integrals. The document also discusses using integrals to estimate the sum of a convergent series.
(i) The document provides solutions to exercises from Chapter 1 of Atiyah and MacDonald's Introduction to Commutative Algebra.
(ii) It works through proofs for various statements about rings, ideals, nilpotent and Jacobson radicals, and the prime and Zariski spectra of rings.
(iii) The solutions cover topics such as when a sum of a nilpotent element and unit is a unit, when a polynomial is a unit or zero divisor based on its coefficients, and properties of the prime and Zariski topologies on the prime spectrum of a ring.
This document defines and discusses properties of the supremum and infimum of sets and functions. It begins by defining upper and lower bounds of sets, and defines the supremum and infimum as the least upper bound and greatest lower bound, respectively. It then proves several properties of the supremum and infimum, including uniqueness, relationships between sets and their suprema/infima, and how operations like addition and scalar multiplication affect suprema and infima. These properties are then extended to functions by defining the supremum and infimum of a function as the supremum and infimum of its range.
This document provides an overview of exponential functions including:
- Definitions of exponential functions for positive integer, rational, and irrational exponents. Conventions are established to define exponents for all real number bases and exponents.
- Properties of exponential functions including that they are continuous functions with domain of all real numbers and range from 0 to infinity. Properties involving addition, subtraction, multiplication, and division of exponents are proven.
- Examples are provided to demonstrate simplifying expressions using properties of exponents, including fractional exponents.
Lesson 13: Exponential and Logarithmic Functions (slides)Matthew Leingang
The document provides an outline and definitions for sections 3.1 and 3.2 of a calculus class, which cover exponential and logarithmic functions. It defines exponential functions, establishes conventions for exponents of all types, and graphs exponential functions. Key points covered include the properties of exponential functions and defining exponents for non-whole number bases.
Exponential functions change addition into multiplication. Different bases for exponentials produce different functions but they share similar characteristics. One base--a number we call e--is an especially good one.
Exponential functions change addition into multiplication. Different bases for exponentials produce different functions but they share similar characteristics. One base--a number we call e--is an especially good one.
Ian.petrow【transcendental number theory】.Tong Leung
This document provides an introduction and overview of the course "Math 249A Fall 2010: Transcendental Number Theory" taught by Kannan Soundararajan. It discusses topics that will be covered, including proving that specific numbers like e, π, and combinations of them are transcendental. Theorems are presented on approximating algebraic numbers and showing linear independence of exponential functions of algebraic numbers. Examples are given of using an integral technique to derive contradictions and prove transcendence.
The document introduces the integral test, which can be used to determine if an infinite series is convergent or divergent. The integral test states that a series is convergent if the corresponding improper integral converges, and divergent if the improper integral diverges. Several examples demonstrate applying the integral test to various series by setting up and evaluating the corresponding improper integrals. The document also discusses using integrals to estimate the sum of a convergent series.
(i) The document provides solutions to exercises from Chapter 1 of Atiyah and MacDonald's Introduction to Commutative Algebra.
(ii) It works through proofs for various statements about rings, ideals, nilpotent and Jacobson radicals, and the prime and Zariski spectra of rings.
(iii) The solutions cover topics such as when a sum of a nilpotent element and unit is a unit, when a polynomial is a unit or zero divisor based on its coefficients, and properties of the prime and Zariski topologies on the prime spectrum of a ring.
This document defines and discusses properties of the supremum and infimum of sets and functions. It begins by defining upper and lower bounds of sets, and defines the supremum and infimum as the least upper bound and greatest lower bound, respectively. It then proves several properties of the supremum and infimum, including uniqueness, relationships between sets and their suprema/infima, and how operations like addition and scalar multiplication affect suprema and infima. These properties are then extended to functions by defining the supremum and infimum of a function as the supremum and infimum of its range.
This document provides an overview of convex optimization. It begins by explaining that convex optimization can efficiently find global optima for certain functions called convex functions. It then defines convex sets as sets where linear combinations of points in the set are also in the set. Common examples of convex sets include norm balls and positive semidefinite matrices. Convex functions are defined as functions where linear combinations of points on the graph lie below the line connecting those points. Convex functions have properties like their first and second derivatives satisfying certain inequalities, allowing efficient optimization.
This document summarizes various tests that can be used to determine if an infinite series converges or diverges, including:
1) The divergence test, integral test, p-series test, comparison test, limit comparison test, alternating series test, and ratio test.
2) It also discusses power series, including determining the radius of convergence and using Taylor series approximations with Taylor's inequality to estimate the remainder term.
3) Key concepts are that convergence tests check if partial sums approach a limit, while divergence tests examine the behavior of individual terms, and that power series have a radius of convergence determining the interval on which they converge.
This document contains the solutions to 12 problems regarding metric spaces and concepts such as open/closed sets, convergence of sequences, limits, and completeness.
In problem 4, it is shown that the set S = {(x,y) | x > y} is open in R^2 by showing its complement is closed. Problem 6 shows the set S = {(x,y) | x*y = 1, x > 0} is closed in R^2 by taking limits of sequences in S. Problem 8 proves a claim about permutations of convergent sequences. Problem 9 shows equivalence between convergence of sequences {pn} and {sn} where sn alternates between pn and a fixed point p.
Other problems
The document discusses limits and the limit laws. It introduces the concept of a limit using an "error-tolerance" game. It then proves some basic limits, such as the limit of x as x approaches a equals a, and the limit of a constant c equals c. It also proves the limit laws, such as the fact that limits can be combined using arithmetic operations and the rules for limits of quotients and roots.
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Matthew Leingang
The exponential function is pretty much the only function whose derivative is itself. The derivative of the natural logarithm function is also beautiful as it fills in an important gap. Finally, the technique of logarithmic differentiation allows us to find derivatives without the product rule.
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.
Lesson 15: Exponential Growth and Decay (slides)Matthew Leingang
Many problems in nature are expressible in terms of a certain differential equation that has a solution in terms of exponential functions. We look at the equation in general and some fun applications, including radioactivity, cooling, and interest.
1) The document provides an overview of continuity, including defining continuity as a function having a limit equal to its value at a point.
2) It discusses several theorems related to continuity, such as the sum of continuous functions being continuous and various trigonometric, exponential, and logarithmic functions being continuous on their domains.
3) The document also covers inverse trigonometric functions and their domains of continuity.
Lesson 2: A Catalog of Essential Functions (slides)Matthew Leingang
This document provides an overview of different types of functions including: linear, polynomial, rational, power, trigonometric, and exponential functions. It discusses representing functions verbally, numerically, visually, and symbolically. Key topics covered include transformations of functions through shifting graphs vertically and horizontally, as well as composing multiple functions.
The famous Kruskal's tree theorem states that the collection of finite trees labelled over a well quasi order and ordered by homeomorphic embedding, forms a well quasi order. Its intended mathematical meaning is that the collection of finite, connected and acyclic graphs labelled over a well quasi order is a well quasi order when it is ordered by the graph minor relation.
Oppositely, the standard proof(s) shows the property to hold for trees in the Computer Science's sense together with an ad-hoc, inductive notion of embedding. The mathematical result follows as a consequence in a somewhat unsatisfactory way.
In this talk, a variant of the standard proof will be illustrated explaining how the Computer Science and the graph-theoretical statements are strictly coupled, thus explaining why the double statement is justified and necessary.
I. A power series is a polynomial with infinitely many terms of the form Σn=0∞anxn.
II. The radius of convergence R determines the values of x where a power series converges absolutely (for |x|<R), diverges (for |x|>R), or may converge or diverge (for |x|=R).
III. Tests like the ratio test and root test can be used to calculate the radius of convergence R.
The document defines and provides examples of rings and ideals. Some key points:
- A ring consists of a set with operations of addition and multiplication satisfying certain properties like commutativity and associativity.
- Common examples of rings include the integers, rational numbers, real numbers, polynomials, and matrices.
- An ideal is a subset of a ring that is closed under addition and multiplication. Ideals play an important role in ring theory.
- Given an ideal I of a ring R, a quotient ring R/I can be constructed by identifying elements of R that differ by an element of I. Operations are defined on these equivalence classes.
The real number system contains rational numbers like integers and fractions, as well as irrational numbers like the square root of 2. It is a complete system where every non-empty set that is bounded above has a least upper bound. This property of completeness is what allows real numbers to correspond precisely to points on a number line. The Archimedean property, which follows from completeness, states that between any real number and zero there is a positive integer multiple. This implies that rational numbers are dense within the real numbers.
The document discusses inference rules for quantifiers in discrete mathematics. It provides examples of using universal instantiation, universal generalization, existential instantiation, and existential generalization. It also discusses the rules of universal specification and universal generalization in more detail with examples. Finally, it presents proofs involving quantifiers over integers to demonstrate techniques like direct proof, proof by contradiction, and proving statements' contrapositives.
This document provides an outline for a calculus lecture on basic differentiation rules. It includes objectives to understand key rules like the constant multiple rule, sum rule, and derivatives of sine and cosine. Examples are worked through to find the derivatives of functions like squaring, cubing, square root, and cube root using the definition of the derivative. Graphs and properties of derived functions are also discussed.
This document discusses ideals and factor rings. It begins by defining an ideal as a subring of a ring where certain multiplication rules hold. It provides examples of ideals in various rings. It then discusses the existence of factor rings when a subring is an ideal. The elements of a factor ring are cosets of the ideal. It provides examples of computing operations in specific factor rings. Finally, it discusses prime and maximal ideals and their relationship to the structure of factor rings.
Lesson 14: Derivatives of Exponential and Logarithmic Functions (Section 041 ...Matthew Leingang
This document is a lecture on derivatives of exponential and logarithmic functions from a Calculus I class at New York University. It covers the objectives and outline, which include finding derivatives of exponential functions with any base, logarithmic functions with any base, and using logarithmic differentiation. It provides proofs and examples of finding derivatives, such as the derivative of the natural exponential function being itself and the derivative of the natural logarithm function.
This document provides an introduction to derivatives, including the different types. It discusses how derivatives allow companies and individuals to transfer unwanted risk to other parties. The main types of derivatives covered are options, forwards, futures, and swaps. Options give the buyer the right but not obligation to buy or sell an asset at a future date. Forwards involve an obligation to buy or sell an asset at a future date. Futures are like forwards but trade on an organized exchange. Swaps involve exchanging cash flows between two parties. Overall, the document provides a high-level overview of derivatives and their use in managing financial risk.
This document contains lecture notes on differentiation rules from a Calculus I class at New York University. It begins with objectives to understand basic differentiation rules like the derivative of a constant function, the Constant Multiple Rule, the Sum Rule, and derivatives of sine and cosine. It then provides examples of using the definition of the derivative to find the derivatives of squaring and cubing functions. It illustrates the functions and their derivatives on graphs and discusses properties like a function being increasing when its derivative is positive.
After defining the limit and calculating a few, we introduced the limit laws. Today we do the same for the derivative. We calculate a few and introduce laws which allow us to computer more. The Power Rule shows us how to compute derivatives of polynomials, and we can also find directly the derivative of sine and cosine.
This document provides an overview of convex optimization. It begins by explaining that convex optimization can efficiently find global optima for certain functions called convex functions. It then defines convex sets as sets where linear combinations of points in the set are also in the set. Common examples of convex sets include norm balls and positive semidefinite matrices. Convex functions are defined as functions where linear combinations of points on the graph lie below the line connecting those points. Convex functions have properties like their first and second derivatives satisfying certain inequalities, allowing efficient optimization.
This document summarizes various tests that can be used to determine if an infinite series converges or diverges, including:
1) The divergence test, integral test, p-series test, comparison test, limit comparison test, alternating series test, and ratio test.
2) It also discusses power series, including determining the radius of convergence and using Taylor series approximations with Taylor's inequality to estimate the remainder term.
3) Key concepts are that convergence tests check if partial sums approach a limit, while divergence tests examine the behavior of individual terms, and that power series have a radius of convergence determining the interval on which they converge.
This document contains the solutions to 12 problems regarding metric spaces and concepts such as open/closed sets, convergence of sequences, limits, and completeness.
In problem 4, it is shown that the set S = {(x,y) | x > y} is open in R^2 by showing its complement is closed. Problem 6 shows the set S = {(x,y) | x*y = 1, x > 0} is closed in R^2 by taking limits of sequences in S. Problem 8 proves a claim about permutations of convergent sequences. Problem 9 shows equivalence between convergence of sequences {pn} and {sn} where sn alternates between pn and a fixed point p.
Other problems
The document discusses limits and the limit laws. It introduces the concept of a limit using an "error-tolerance" game. It then proves some basic limits, such as the limit of x as x approaches a equals a, and the limit of a constant c equals c. It also proves the limit laws, such as the fact that limits can be combined using arithmetic operations and the rules for limits of quotients and roots.
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Matthew Leingang
The exponential function is pretty much the only function whose derivative is itself. The derivative of the natural logarithm function is also beautiful as it fills in an important gap. Finally, the technique of logarithmic differentiation allows us to find derivatives without the product rule.
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.
Lesson 15: Exponential Growth and Decay (slides)Matthew Leingang
Many problems in nature are expressible in terms of a certain differential equation that has a solution in terms of exponential functions. We look at the equation in general and some fun applications, including radioactivity, cooling, and interest.
1) The document provides an overview of continuity, including defining continuity as a function having a limit equal to its value at a point.
2) It discusses several theorems related to continuity, such as the sum of continuous functions being continuous and various trigonometric, exponential, and logarithmic functions being continuous on their domains.
3) The document also covers inverse trigonometric functions and their domains of continuity.
Lesson 2: A Catalog of Essential Functions (slides)Matthew Leingang
This document provides an overview of different types of functions including: linear, polynomial, rational, power, trigonometric, and exponential functions. It discusses representing functions verbally, numerically, visually, and symbolically. Key topics covered include transformations of functions through shifting graphs vertically and horizontally, as well as composing multiple functions.
The famous Kruskal's tree theorem states that the collection of finite trees labelled over a well quasi order and ordered by homeomorphic embedding, forms a well quasi order. Its intended mathematical meaning is that the collection of finite, connected and acyclic graphs labelled over a well quasi order is a well quasi order when it is ordered by the graph minor relation.
Oppositely, the standard proof(s) shows the property to hold for trees in the Computer Science's sense together with an ad-hoc, inductive notion of embedding. The mathematical result follows as a consequence in a somewhat unsatisfactory way.
In this talk, a variant of the standard proof will be illustrated explaining how the Computer Science and the graph-theoretical statements are strictly coupled, thus explaining why the double statement is justified and necessary.
I. A power series is a polynomial with infinitely many terms of the form Σn=0∞anxn.
II. The radius of convergence R determines the values of x where a power series converges absolutely (for |x|<R), diverges (for |x|>R), or may converge or diverge (for |x|=R).
III. Tests like the ratio test and root test can be used to calculate the radius of convergence R.
The document defines and provides examples of rings and ideals. Some key points:
- A ring consists of a set with operations of addition and multiplication satisfying certain properties like commutativity and associativity.
- Common examples of rings include the integers, rational numbers, real numbers, polynomials, and matrices.
- An ideal is a subset of a ring that is closed under addition and multiplication. Ideals play an important role in ring theory.
- Given an ideal I of a ring R, a quotient ring R/I can be constructed by identifying elements of R that differ by an element of I. Operations are defined on these equivalence classes.
The real number system contains rational numbers like integers and fractions, as well as irrational numbers like the square root of 2. It is a complete system where every non-empty set that is bounded above has a least upper bound. This property of completeness is what allows real numbers to correspond precisely to points on a number line. The Archimedean property, which follows from completeness, states that between any real number and zero there is a positive integer multiple. This implies that rational numbers are dense within the real numbers.
The document discusses inference rules for quantifiers in discrete mathematics. It provides examples of using universal instantiation, universal generalization, existential instantiation, and existential generalization. It also discusses the rules of universal specification and universal generalization in more detail with examples. Finally, it presents proofs involving quantifiers over integers to demonstrate techniques like direct proof, proof by contradiction, and proving statements' contrapositives.
This document provides an outline for a calculus lecture on basic differentiation rules. It includes objectives to understand key rules like the constant multiple rule, sum rule, and derivatives of sine and cosine. Examples are worked through to find the derivatives of functions like squaring, cubing, square root, and cube root using the definition of the derivative. Graphs and properties of derived functions are also discussed.
This document discusses ideals and factor rings. It begins by defining an ideal as a subring of a ring where certain multiplication rules hold. It provides examples of ideals in various rings. It then discusses the existence of factor rings when a subring is an ideal. The elements of a factor ring are cosets of the ideal. It provides examples of computing operations in specific factor rings. Finally, it discusses prime and maximal ideals and their relationship to the structure of factor rings.
Lesson 14: Derivatives of Exponential and Logarithmic Functions (Section 041 ...Matthew Leingang
This document is a lecture on derivatives of exponential and logarithmic functions from a Calculus I class at New York University. It covers the objectives and outline, which include finding derivatives of exponential functions with any base, logarithmic functions with any base, and using logarithmic differentiation. It provides proofs and examples of finding derivatives, such as the derivative of the natural exponential function being itself and the derivative of the natural logarithm function.
This document provides an introduction to derivatives, including the different types. It discusses how derivatives allow companies and individuals to transfer unwanted risk to other parties. The main types of derivatives covered are options, forwards, futures, and swaps. Options give the buyer the right but not obligation to buy or sell an asset at a future date. Forwards involve an obligation to buy or sell an asset at a future date. Futures are like forwards but trade on an organized exchange. Swaps involve exchanging cash flows between two parties. Overall, the document provides a high-level overview of derivatives and their use in managing financial risk.
This document contains lecture notes on differentiation rules from a Calculus I class at New York University. It begins with objectives to understand basic differentiation rules like the derivative of a constant function, the Constant Multiple Rule, the Sum Rule, and derivatives of sine and cosine. It then provides examples of using the definition of the derivative to find the derivatives of squaring and cubing functions. It illustrates the functions and their derivatives on graphs and discusses properties like a function being increasing when its derivative is positive.
After defining the limit and calculating a few, we introduced the limit laws. Today we do the same for the derivative. We calculate a few and introduce laws which allow us to computer more. The Power Rule shows us how to compute derivatives of polynomials, and we can also find directly the derivative of sine and cosine.
The document introduces approximations of the area under a curve using Riemann sums with rectangles. It explains left and right Riemann sums, showing how to calculate them by dividing the area into equal subintervals and determining the height of each rectangle. While Riemann sums provide approximations, taking the widths of the subintervals to zero provides the exact area under a curve, as shown in a video clip about the concept. Riemann sums have applications in economics for determining consumer surplus and in science for modeling phenomena like blood flow.
This document discusses functions, limits, and continuity. It begins by defining functions, domains, ranges, and some standard real functions like constant, identity, modulus, and greatest integer functions. It then covers limits of functions including one-sided limits and properties of limits. Examples are provided to illustrate evaluating limits using substitution and factorization methods. The overall objectives are to understand functions, domains, ranges, limits of functions and methods to evaluate limits.
1) The document discusses the chain rule and higher derivatives in calculus. It defines the chain rule and provides examples of applying it to find the derivative of composite functions.
2) It also explains how to take higher derivatives by applying the derivative operator multiple times, and gives an example of finding the nth derivative of xn.
3) Additional examples are provided of using the chain rule to find derivatives of more complex expressions involving radicals, quotients, and other functions.
1) The document discusses basic rules and concepts of integration, including that integration is the inverse process of differentiation and that the indefinite integral of a function f(x) is notated as ∫f(x) dx = F(x) + c, where F(x) is the primitive function and c is the constant of integration.
2) Methods of integration discussed include the substitution method, where a function is substituted for the variable, and integration by parts, which uses the product rule in reverse to solve integrals involving products.
3) Finding the constant of integration c requires knowing the value of the primitive function F(x) at a specific point, which eliminates the family of functions and isolates a
The document discusses various calculus concepts including:
- Indefinite integrals and finding antiderivatives
- Definite integrals and properties such as linearity and changing limits of integration
- Integrals of trigonometric functions including sine, cosine, tangent, cotangent, secant, and cosecant
It provides examples to illustrate each concept discussed.
1) The document discusses differential calculus and introduces concepts like gradients, tangents, and derivatives.
2) It explains that the gradient of a function at a point is defined as the gradient of the tangent line to the function at that point.
3) The document demonstrates finding gradients of linear functions using the two-point formula, and how to approximate the gradient of a nonlinear function like a parabola by considering secants that approach the tangent line.
Benginning Calculus Lecture notes 15 - techniques of integrationbasyirstar
This document is a lecture on integration techniques including integration by parts and partial fractions. It introduces the formula for integration by parts and provides examples of applying the technique. It also explains the method of partial fractions for rewriting rational functions as a sum of simpler fractions and includes examples of using partial fractions. The goal is for students to learn how to apply techniques of integration like algebraic procedures, integration by parts, and partial fractions.
The document discusses limits and continuity, explaining what limits are, how to evaluate different types of limits using techniques like direct substitution, dividing out, and rationalizing, and how limits relate to concepts like derivatives, continuity, discontinuities, and the intermediate value theorem. Special trig limits, properties of limits, and how limits can be used to find derivatives are also covered.
This document discusses integration, which is the inverse process of differentiation. Integration allows us to find the original function given its derivative. Several integration techniques are explained, including substitution, integration by parts, and finding volumes of revolution. Standard integrals are presented along with examples of calculating areas under curves and volumes obtained by rotating areas about axes. Definite integrals are used to find the area between curves over a specified interval.
The document discusses key concepts related to limits, continuity, and differentiation. It defines what it means for a variable x to approach a finite number a or infinity, and provides the formal definitions of one-sided limits and two-sided limits. It also discusses indeterminate forms when limits take on forms like 0/0, infinity/infinity, or infinity - infinity. The document outlines several properties of limits, including limits of even and odd functions. It distinguishes between the limit of a function as x approaches a, denoted limx→af(x), versus the function value at that point, f(a). Finally, it states standard theorems about limits, such as the sum and product of two functions whose limits exist
Benginning Calculus Lecture notes 12 - anti derivatives indefinite and defini...basyirstar
This document provides an overview of beginning calculus concepts related to antiderivatives, definite integrals, and computing areas under curves. It discusses evaluating antiderivatives using substitution and guessing methods. It also explains how to compute definite integrals using Riemann sums and taking the limit of partition widths approaching zero. Examples are provided to illustrate computing areas under curves for basic functions like polynomials and finding net areas when functions are sometimes positive and sometimes negative.
This document covers key topics in calculus including derivatives, limits, and their applications. It discusses the definition of derivatives and common derivative rules like the product rule, quotient rule, and chain rule. It also addresses limits, including the limit evaluation method of factoring and canceling, L'Hopital's rule, and evaluating limits at positive and negative infinity. The document appears to be a study guide or reference sheet for calculus concepts from derivatives to limits.
The document discusses key concepts related to derivatives using flashcards. It covers concave up and down parabolas, instantaneous velocity and acceleration as derivatives and anti-derivatives of position and acceleration functions, and defines average velocity as the change in position over time and average acceleration as the change in velocity over time.
This document discusses several topics related to calculus including:
1) Derivatives of position, velocity, and acceleration and how they relate to each other.
2) An example problem calculating velocity from a position function.
3) The Mean Value Theorem and how to apply it to find critical points of a function.
4) How the first and second derivatives of a function relate to critical points, maxima, minima, and points of inflection or concavity.
5) Related rates problems and how to set them up using derivatives and relationships between variables.
Exponential functions change addition into multiplication. Different bases for exponentials produce different functions but they share similar characteristics. One base--a number we call e--is an especially good one.
This document defines and explains exponential functions. It begins by defining an as a positive whole number and discusses properties like ax+y = ax * ay. It introduces conventions to define exponential functions for non-positive whole number exponents, like defining a0 = 1 and a-n = 1/an. It discusses graphs of various exponential functions and limits of exponential functions as x approaches positive or negative infinity. The document then discusses the natural exponential function and introduces the number e through the concept of compound interest calculations.
This document provides an overview of epsilon-related proofs in real analysis. It defines key concepts such as convergent sequences, open and closed sets, and continuity using epsilon-neighborhoods. For convergent sequences, a sequence converges to a real number if it can be made arbitrarily close to that number as the number of terms increases. A set is open if every point has an epsilon-neighborhood contained within the set, and closed if it contains all its limit points. Continuity is defined as a function remaining arbitrarily close to its value at a point as the input gets arbitrarily close to that point. Examples are provided to illustrate these definitions.
This document provides information about exponential functions:
- Exponential functions are defined as f(x) = ax, where a is a positive number called the base.
- The graphs of exponential functions with a base greater than 1 grow exponentially to the right, while graphs with a base between 0 and 1 slope down as they move to the right.
- Exponential functions are one-to-one and onto, appearing in processes like population growth, interest rates, and carbon dating.
This document discusses sequences and series of numbers. It begins by introducing sequences and the concept of convergence for sequences. A sequence converges to a limit L if, given any positive number ε, there exists an N such that the terms an of the sequence satisfy |L - an| < ε for all n > N.
It then proves some basic properties of convergence, including that a convergent sequence must be bounded, and that limits are preserved under operations. Cauchy's criterion for convergence is introduced - a sequence is Cauchy if given any ε, there exists an N such that |am - an| < ε for all m, n > N. Every convergent sequence is Cauchy, and C
This document defines exponents and radicals. It discusses exponential notation, zero and negative exponents, and the laws of exponents. It also covers scientific notation, nth roots, rational exponents, and rationalizing the denominator. The objectives are to define integer exponents and exponential notation, zero and negative exponents, identify laws of exponents, write numbers using scientific notation, and define nth roots and rational exponents.
This document discusses several mathematical topics related to analysis, algebra, and geometry. It defines p-adic numbers as the completion of rational numbers with respect to the p-adic valuation. It also defines the p-adic valuation, chain complexes, derived functors, partial differential operators, and Picard's theorems regarding complex functions taking on every value. Additionally, it provides brief definitions for concepts like parabolic subgroups, the Picard variety, and the Picard-Lefschetz theory.
Discrete structures & optimization unit 1SURBHI SAROHA
This document provides an overview of mathematical logic and related concepts. It discusses propositional and predicate logic, including truth tables for logical connectives like AND, OR, and NOT. It also covers topics like normal forms, quantifiers, and rules of inference. Specifically, it defines disjunctive normal form (DNF) and conjunctive normal form (CNF), and gives examples of quantified statements using universal and existential quantifiers. It also provides examples of nested quantifiers and discusses how rules of inference can be used to construct valid arguments.
The document discusses the basic proportionality theorem in geometry. It states that if a line is drawn parallel to one side of a triangle, intersecting the other two sides, the lengths of the segments of those two sides will be divided in the same ratio. This is also known as Thales' theorem, after the Greek mathematician who discovered it. The document also provides proofs of both the theorem and its converse.
Lesson 14: Derivatives of Logarithmic and Exponential Functions (slides)Mel Anthony Pepito
This document provides an overview of the key points covered in a calculus lecture on derivatives of logarithmic and exponential functions:
1) It discusses the derivatives of exponential functions with any base, as well as the derivatives of logarithmic functions with any base.
2) It covers using the technique of logarithmic differentiation to find derivatives of functions involving products, quotients, and/or exponentials.
3) The document provides examples of finding derivatives of various logarithmic and exponential functions.
Given two positive integers a and b, there exist unique integers q and r such that a = bq + r, where 0 ≤ r < b. This is known as the division algorithm from elementary number theory.
- The document discusses exchanging more than just complete data between databases, by using representation systems that can capture sets of possible instances.
- It proposes a formalism for exchanging representations between systems and applies this to incomplete instances and knowledge bases.
- Incomplete instances like those with null values or constraints can be represented as representation systems, and positive conditional instances form a strong representation system for schema mappings specified by source-to-target tuple-generating dependencies.
The document discusses properties of equalities and inequalities as well as how to solve linear equations and inequalities with one variable. It introduces properties of equality like the addition, subtraction, multiplication, and division properties. It also covers properties of operations like the commutative, associative, and distributive properties. Properties of inequality are presented along with how to use properties to solve equations and inequalities with one variable by manipulating and isolating the variable. Examples are provided to demonstrate solving linear equations and graphing solutions to linear inequalities on a number line.
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Here are the steps to solve the integrals:
1) ∫ 3x dx = 3x^2/2 + C
2) ∫ 3x+3 dx = 3x^2/2 + 9x + C
3) ∫ -2 cos x dx = -2 sin x + C
4) ∫ 23/x dx = 2x + C
5) ∫ x-7 dx = (x-7)^2/2 + C
6) ∫ 3x + 7 dx = 3x^2/2 + 7x + C
7) ∫ e^x - 1/9x dx = e^x - 9x + C
8)
In this slide i am trying my best to describe about the power series. If you face any problem or anything that you can't understand please contact me on facebook:https://www.facebook.com/asadujjaman.asad.79
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Lesson 13: Exponential and Logarithmic Functions (slides)
1. Sec on 3.1–3.2
Exponen al and Logarithmic
Func ons
V63.0121.001: Calculus I
Professor Ma hew Leingang
New York University
March 9, 2011
.
2. Announcements
Midterm is graded.
average = 44, median=46,
SD =10
There is WebAssign due
a er Spring Break.
Quiz 3 on 2.6, 2.8, 3.1, 3.2
on March 30
3. Midterm Statistics
Average: 43.86/60 = 73.1%
Median: 46/60 = 76.67%
Standard Devia on: 10.64%
“good” is anything above average and “great” is anything more
than one standard devia on above average.
More than one SD below the mean is cause for concern.
4. Objectives for Sections 3.1 and 3.2
Know the defini on of an
exponen al func on
Know the proper es of
exponen al func ons
Understand and apply
the laws of logarithms,
including the change of
base formula.
5. Outline
Defini on of exponen al func ons
Proper es of exponen al Func ons
The number e and the natural exponen al func on
Compound Interest
The number e
A limit
Logarithmic Func ons
6. Derivation of exponentials
Defini on
If a is a real number and n is a posi ve whole number, then
an = a · a · · · · · a
n factors
7. Derivation of exponentials
Defini on
If a is a real number and n is a posi ve whole number, then
an = a · a · · · · · a
n factors
Examples
23 = 2 · 2 · 2 = 8
34 = 3 · 3 · 3 · 3 = 81
(−1)5 = (−1)(−1)(−1)(−1)(−1) = −1
8. Anatomy of a power
Defini on
A power is an expression of the form ab .
The number a is called the base.
The number b is called the exponent.
9. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y
a
(ax )y = axy
(ab)x = ax bx
whenever all exponents are posi ve whole numbers.
10. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y (differences to quo ents)
a
(ax )y = axy
(ab)x = ax bx
whenever all exponents are posi ve whole numbers.
11. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y (differences to quo ents)
a
(ax )y = axy (repeated exponen a on to mul plied powers)
(ab)x = ax bx
whenever all exponents are posi ve whole numbers.
12. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y (differences to quo ents)
a
(ax )y = axy (repeated exponen a on to mul plied powers)
(ab)x = ax bx (power of product is product of powers)
whenever all exponents are posi ve whole numbers.
13. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y (differences to quo ents)
a
(ax )y = axy (repeated exponen a on to mul plied powers)
(ab)x = ax bx (power of product is product of powers)
whenever all exponents are posi ve whole numbers.
14. Fact
If a is a real number, then
ax+y = ax ay (sums to products)
x−y ax
a = y (differences to quo ents)
a
(ax )y = axy (repeated exponen a on to mul plied powers)
(ab)x = ax bx (power of product is product of powers)
whenever all exponents are posi ve whole numbers.
Proof.
Check for yourself:
ax+y = a · a · · · · · a = a · a · · · · · a · a · a · · · · · a = ax ay
x + y factors x factors y factors
15. Let’s be conventional
The desire that these proper es remain true gives us
conven ons for ax when x is not a posi ve whole number.
16. Let’s be conventional
The desire that these proper es remain true gives us
conven ons for ax when x is not a posi ve whole number.
For example, what should a0 be?
We would want this to be true:
!
an = an+0 = an · a0
17. Let’s be conventional
The desire that these proper es remain true gives us
conven ons for ax when x is not a posi ve whole number.
For example, what should a0 be?
We would want this to be true:
n
! ! a
an = an+0 = an · a0 =⇒ a0 = n = 1
a
18. Let’s be conventional
The desire that these proper es remain true gives us
conven ons for ax when x is not a posi ve whole number.
For example, what should a0 be?
We would want this to be true:
n
! ! a
an = an+0 = an · a0 =⇒ a0 = n = 1
a
Defini on
If a ̸= 0, we define a0 = 1.
19. Let’s be conventional
The desire that these proper es remain true gives us
conven ons for ax when x is not a posi ve whole number.
For example, what should a0 be?
We would want this to be true:
n
! ! a
an = an+0 = an · a0 =⇒ a0 = n = 1
a
Defini on
If a ̸= 0, we define a0 = 1.
No ce 00 remains undefined (as a limit form, it’s
indeterminate).
21. Conventions for negative exponents
If n ≥ 0, we want
a0 1
an+(−n) = an · a−n =⇒ a−n =
! !
= n
an a
22. Conventions for negative exponents
If n ≥ 0, we want
a0 1
an+(−n) = an · a−n =⇒ a−n =
! !
= n
an a
Defini on
1
If n is a posi ve integer, we define a−n = .
an
23. Defini on
1
If n is a posi ve integer, we define a−n = .
an
24. Defini on
1
If n is a posi ve integer, we define a−n = .
an
Fact
1
The conven on that a−n = “works” for nega ve n as well.
an
m−n am
If m and n are any integers, then a = n.
a
26. Conventions for fractional exponents
If q is a posi ve integer, we want
! ! √
(a1/q )q = a1 = a =⇒ a1/q = q
a
27. Conventions for fractional exponents
If q is a posi ve integer, we want
! ! √
(a1/q )q = a1 = a =⇒ a1/q = q
a
Defini on
√
If q is a posi ve integer, we define a1/q = q
a. We must have a ≥ 0
if q is even.
28. Conventions for fractional exponents
If q is a posi ve integer, we want
! ! √
(a1/q )q = a1 = a =⇒ a1/q = q
a
Defini on
√
If q is a posi ve integer, we define a1/q = q a. We must have a ≥ 0
if q is even.
√q
(√ )p
No ce that ap = q a . So we can unambiguously say
ap/q = (ap )1/q = (a1/q )p
30. Conventions for irrational
exponents
So ax is well-defined if a is posi ve and x is ra onal.
What about irra onal powers?
Defini on
Let a > 0. Then
ax = lim ar
r→x
r ra onal
31. Conventions for irrational
exponents
So ax is well-defined if a is posi ve and x is ra onal.
What about irra onal powers?
Defini on
Let a > 0. Then
ax = lim ar
r→x
r ra onal
In other words, to approximate ax for irra onal x, take r close to x
but ra onal and compute ar .
32. Approximating a power with an
irrational exponent
r 2r
3 23
√=8
10
3.1 231/10 = √ 31 ≈ 8.57419
2
100
3.14 2314/100 = √ 314 ≈ 8.81524
2
1000
3.141 23141/1000 = 23141 ≈ 8.82135
The limit (numerically approximated is)
2π ≈ 8.82498
39. Graphs of exponential functions
y
y = (1/2)x y = 10x 3x = 2x
y= y y = 1.5x
y = 1x
. x
40. Graphs of exponential functions
y
y = (y/= x(1/3)x
1 2) y = 10x 3x = 2x
y= y y = 1.5x
y = 1x
. x
41. Graphs of exponential functions
y
y = (y/= x(1/3)x
1 2) y = (1/10y x= 10x 3x = 2x
) y= y y = 1.5x
y = 1x
. x
42. Graphs of exponential functions
y
y y =y/=3(1/3)x
= (1(2/x)x
2) y = (1/10y x= 10x 3x = 2x
) y= y y = 1.5x
y = 1x
. x
43. Outline
Defini on of exponen al func ons
Proper es of exponen al Func ons
The number e and the natural exponen al func on
Compound Interest
The number e
A limit
Logarithmic Func ons
44. Properties of exponential Functions
Theorem
If a > 0 and a ̸= 1, then f(x) = ax is a con nuous func on with
domain (−∞, ∞) and range (0, ∞). In par cular, ax > 0 for all x.
For any real numbers x and y, and posi ve numbers a and b we have
ax+y = ax ay
x−y ax
a = y
a
(a ) = axy
x y
(ab)x = ax bx
45. Properties of exponential Functions
Theorem
If a > 0 and a ̸= 1, then f(x) = ax is a con nuous func on with
domain (−∞, ∞) and range (0, ∞). In par cular, ax > 0 for all x.
For any real numbers x and y, and posi ve numbers a and b we have
ax+y = ax ay
x−y ax
a = y (nega ve exponents mean reciprocals)
a
(a ) = axy
x y
(ab)x = ax bx
46. Properties of exponential Functions
Theorem
If a > 0 and a ̸= 1, then f(x) = ax is a con nuous func on with
domain (−∞, ∞) and range (0, ∞). In par cular, ax > 0 for all x.
For any real numbers x and y, and posi ve numbers a and b we have
ax+y = ax ay
x−y ax
a = y (nega ve exponents mean reciprocals)
a
(a ) = axy (frac onal exponents mean roots)
x y
(ab)x = ax bx
47. Proof.
This is true for posi ve integer exponents by natural defini on
Our conven onal defini ons make these true for ra onal
exponents
Our limit defini on make these for irra onal exponents, too
53. Limits of exponential functions
Fact (Limits of exponen al
func ons) y
y (1 y )/3 x
y = =/(1= )(2/3)x y = y1/1010= 2x = 1.5
2
x
( = =x 3x y
y ) x
y
If a > 1, then
lim ax = ∞ and
x→∞
lim ax = 0
x→−∞
If 0 < a < 1, then y = 1x
lim ax = 0 and . x
x→∞
lim ax = ∞
x→−∞
54. Outline
Defini on of exponen al func ons
Proper es of exponen al Func ons
The number e and the natural exponen al func on
Compound Interest
The number e
A limit
Logarithmic Func ons
55. Compounded Interest
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded once a year. How much do you have A er one year?
A er two years? A er t years?
56. Compounded Interest
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded once a year. How much do you have A er one year?
A er two years? A er t years?
Answer
$100 + 10% = $110
57. Compounded Interest
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded once a year. How much do you have A er one year?
A er two years? A er t years?
Answer
$100 + 10% = $110
$110 + 10% = $110 + $11 = $121
58. Compounded Interest
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded once a year. How much do you have A er one year?
A er two years? A er t years?
Answer
$100 + 10% = $110
$110 + 10% = $110 + $11 = $121
$100(1.1)t .
59. Compounded Interest: quarterly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded four mes a year. How much do you have A er one
year? A er two years? A er t years?
60. Compounded Interest: quarterly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded four mes a year. How much do you have A er one
year? A er two years? A er t years?
Answer
$100(1.025)4 = $110.38,
61. Compounded Interest: quarterly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded four mes a year. How much do you have A er one
year? A er two years? A er t years?
Answer
$100(1.025)4 = $110.38, not $100(1.1)4 !
62. Compounded Interest: quarterly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded four mes a year. How much do you have A er one
year? A er two years? A er t years?
Answer
$100(1.025)4 = $110.38, not $100(1.1)4 !
$100(1.025)8 = $121.84
63. Compounded Interest: quarterly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded four mes a year. How much do you have A er one
year? A er two years? A er t years?
Answer
$100(1.025)4 = $110.38, not $100(1.1)4 !
$100(1.025)8 = $121.84
$100(1.025)4t .
64. Compounded Interest: monthly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded twelve mes a year. How much do you have a er t
years?
65. Compounded Interest: monthly
Ques on
Suppose you save $100 at 10% annual interest, with interest
compounded twelve mes a year. How much do you have a er t
years?
Answer
$100(1 + 10%/12)12t
66. Compounded Interest: general
Ques on
Suppose you save P at interest rate r, with interest compounded n
mes a year. How much do you have a er t years?
67. Compounded Interest: general
Ques on
Suppose you save P at interest rate r, with interest compounded n
mes a year. How much do you have a er t years?
Answer
( r )nt
B(t) = P 1 +
n
68. Compounded Interest: continuous
Ques on
Suppose you save P at interest rate r, with interest compounded
every instant. How much do you have a er t years?
69. Compounded Interest: continuous
Ques on
Suppose you save P at interest rate r, with interest compounded
every instant. How much do you have a er t years?
Answer
( ( )rnt
r )nt 1
B(t) = lim P 1 + = lim P 1 +
n→∞ n n→∞ n
[ ( )n ]rt
1
= P lim 1 +
n→∞ n
independent of P, r, or t
74. Existence of e
See Appendix B
( )n
1
n 1+
n
1 2
2 2.25
3 2.37037
10 2.59374
75. Existence of e
See Appendix B
( )n
1
n 1+
n
1 2
2 2.25
3 2.37037
10 2.59374
100 2.70481
76. Existence of e
See Appendix B
( )n
1
n 1+
n
1 2
2 2.25
3 2.37037
10 2.59374
100 2.70481
1000 2.71692
77. Existence of e
See Appendix B
( )n
1
n 1+
n
1 2
2 2.25
3 2.37037
10 2.59374
100 2.70481
1000 2.71692
106 2.71828
78. Existence of e
See Appendix B
( )n
1
n 1+
We can experimentally n
verify that this number 1 2
exists and is 2 2.25
3 2.37037
e ≈ 2.718281828459045 . . .
10 2.59374
100 2.70481
1000 2.71692
106 2.71828
79. Existence of e
See Appendix B
( )n
1
n 1+
We can experimentally n
verify that this number 1 2
exists and is 2 2.25
3 2.37037
e ≈ 2.718281828459045 . . .
10 2.59374
e is irra onal 100 2.70481
1000 2.71692
106 2.71828
80. Existence of e
See Appendix B
( )n
1
n 1+
We can experimentally n
verify that this number 1 2
exists and is 2 2.25
3 2.37037
e ≈ 2.718281828459045 . . .
10 2.59374
e is irra onal 100 2.70481
1000 2.71692
e is transcendental
106 2.71828
81. Meet the Mathematician: Leonhard Euler
Born in Switzerland, lived
in Prussia (Germany) and
Russia
Eyesight trouble all his
life, blind from 1766
onward
Hundreds of
contribu ons to calculus,
number theory, graph
theory, fluid mechanics, Leonhard Paul Euler
op cs, and astronomy Swiss, 1707–1783
83. A limit
Ques on
eh − 1
What is lim ?
h→0 h
Answer
e = lim (1 + 1/n)n = lim (1 + h)1/h . So for a small h,
n→∞ h→0
e ≈ (1 + h) 1/h
. So
[ ]h
eh − 1 (1 + h)1/h − 1
≈ =1
h h
84. A limit
eh − 1
It follows that lim = 1.
h→0 h
2h − 1
This can be used to characterize e: lim = 0.693 · · · < 1
h→0 h
3h − 1
and lim = 1.099 · · · > 1
h→0 h
85. Outline
Defini on of exponen al func ons
Proper es of exponen al Func ons
The number e and the natural exponen al func on
Compound Interest
The number e
A limit
Logarithmic Func ons
86. Logarithms
Defini on
The base a logarithm loga x is the inverse of the func on ax
y = loga x ⇐⇒ x = ay
The natural logarithm ln x is the inverse of ex . So
y = ln x ⇐⇒ x = ey .
96. Graphs of logarithmic functions
y
y =y3= 2x
x
y = log2 x
y = log3 x
(0, 1)
.
(1, 0) x
97. Graphs of logarithmic functions
y
y =y10y3= 2x
=x x
y = log2 x
y = log3 x
(0, 1)
y = log10 x
.
(1, 0) x
98. Graphs of logarithmic functions
y
y =x ex
y =y10y3= 2x
= x
y = log2 x
yy= log3 x
= ln x
(0, 1)
y = log10 x
.
(1, 0) x
99. Change of base formula for logarithms
Fact
logb x
If a > 0 and a ̸= 1, and the same for b, then loga x =
logb a
100. Change of base formula for logarithms
Fact
logb x
If a > 0 and a ̸= 1, and the same for b, then loga x =
logb a
Proof.
If y = loga x, then x = ay
So logb x = logb (ay ) = y logb a
Therefore
logb x
y = loga x =
logb a
102. Example of changing base
Example
Find log2 8 by using log10 only.
Solu on
log10 8 0.90309
log2 8 = ≈ =3
log10 2 0.30103
103. Example of changing base
Example
Find log2 8 by using log10 only.
Solu on
log10 8 0.90309
log2 8 = ≈ =3
log10 2 0.30103
Surprised?
104. Example of changing base
Example
Find log2 8 by using log10 only.
Solu on
log10 8 0.90309
log2 8 = ≈ =3
log10 2 0.30103
Surprised? No, log2 8 = log2 23 = 3 directly.
105. Upshot of changing base
The point of the change of base formula
logb x 1
loga x = = · logb x = constant · logb x
logb a logb a
is that all the logarithmic func ons are mul ples of each other. So
just pick one and call it your favorite.
Engineers like the common logarithm log = log10
Computer scien sts like the binary logarithm lg = log2
Mathema cians like natural logarithm ln = loge
Naturally, we will follow the mathema cians. Just don’t pronounce
it “lawn.”