This document provides an overview of L'Hopital's rule for evaluating limits of indeterminate forms. It begins by defining different types of indeterminate forms such as 0/0, infinity/infinity, 0*infinity, infinity - infinity, and 00. It then introduces L'Hopital's rule, which allows such limits to be evaluated by taking the derivative of the numerator and denominator. Several examples are worked out to demonstrate how L'Hopital's rule can be applied. The document concludes by discussing various types of relative growth rates between functions as x approaches infinity.
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 14: Derivatives of Exponential and Logarithmic Functions (Section 021 ...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 14: Derivatives of Exponential and Logarithmic Functions (Section 021 ...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.
I am Jayson L. I am a Mathematical Statistics Homework Expert at statisticshomeworkhelper.com. I hold a Master's in Statistics, from Liverpool, UK. I have been helping students with their homework for the past 5 years. I solve homework related to Mathematical Statistics.
Visit statisticshomeworkhelper.com or email info@statisticshomeworkhelper.com.You can also call on +1 678 648 4277 for any assistance with Mathematical Statistics Homework.
Finding the Extreme Values with some Application of Derivativesijtsrd
There are many different way of mathematics rules. Among them, we express finding the extreme values for the optimization problems that changes in the particle life with the derivatives. The derivative is the exact rate at which one quantity changes with respect to another. And them, we can compute the profit and loss of a process that a company or a system. Variety of optimization problems are solved by using derivatives. There were use derivatives to find the extreme values of functions, to determine and analyze the shape of graphs and to find numerically where a function equals zero. Kyi Sint | Kay Thi Win "Finding the Extreme Values with some Application of Derivatives" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29347.pdf Paper URL: https://www.ijtsrd.com/mathemetics/other/29347/finding-the-extreme-values-with-some-application-of-derivatives/kyi-sint
In classical data analysis, data are single values. This is the case if you consider a dataset of n patients which age and size you know. But what if you record the blood pressure or the weight of each patient during a day ? Then, for each patient, you do not have a single-valued data but a set of values since the blood pressure or the weight are not constant during the day.
Suppose now that you do not want to record blood pressure a thousand times for each patient and to store it into a database because your memory space is limited. Therefore, you need to aggregate each set of values into symbols: intervals (lower and upper bounds only), box plots, histograms or even distributions (distribution law with mean and variance)...
Thus, the issue is to adapt classical statistical tools to symbolic data analysis. More precisely, this article is aimed at proposing a method to fit a regression on Gaussian distributions. This paper is divided as follows: first, it presents the computation of the maximum likelihood estimator and then it compares the new approach with the usual least squares regression.
I am Vincent S. I am an Algorithm Assignment Expert at programminghomeworkhelp.com. I hold a Ph.D. in Programming from, University of Minnesota, USA. I have been helping students with their homework for the past 9 years. I solve assignments related to Algorithms.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Algorithm assignments.
Nec 602 unit ii Random Variables and Random processDr Naim R Kidwai
The presentation explains concept of Probability, random variable, statistical averages, correlation, sum of random Variables, Central Limit Theorem,
random process, classification of random processes, power spectral density, multiple random processes.
Motivated by presenting mathematics visually and interestingly to common people based on calculus and its extension, parametric curves are explored here to have two and three dimensional objects such that these objects can be used for demonstrating mathematics.
Epicycloid, hypocycloid are particular curves that are implemented in MATLAB programs and the motifs are presented here. The obtained curves are considered to be domains for complex mappings to have new variation of Figures and objects. Additionally Voronoi mapping is also implemented to some parametric curves and some resulting complex mappings.
Some obtained 3 dimensional objects are considered as flowers and animals inspiring to be mathematical ornaments of hypocycloid dance which is also illustrated here.
AACIMP 2010 Summer School lecture by Leonidas Sakalauskas. "Applied Mathematics" stream. "Stochastic Programming and Applications" course. Part 3.
More info at http://summerschool.ssa.org.ua
On New Root Finding Algorithms for Solving Nonlinear Transcendental EquationsAI Publications
In this paper, we present new iterative algorithms to find a root of the given nonlinear transcendental equations. In the proposed algorithms, we use nonlinear Taylor’s polynomial interpolation and a modified error correction term with a fixed-point concept. We also investigated for possible extension of the higher order iterative algorithms in single variable to higher dimension. Several numerical examples are presented to illustrate the proposed algorithms.
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.
I am Jayson L. I am a Mathematical Statistics Homework Expert at statisticshomeworkhelper.com. I hold a Master's in Statistics, from Liverpool, UK. I have been helping students with their homework for the past 5 years. I solve homework related to Mathematical Statistics.
Visit statisticshomeworkhelper.com or email info@statisticshomeworkhelper.com.You can also call on +1 678 648 4277 for any assistance with Mathematical Statistics Homework.
Finding the Extreme Values with some Application of Derivativesijtsrd
There are many different way of mathematics rules. Among them, we express finding the extreme values for the optimization problems that changes in the particle life with the derivatives. The derivative is the exact rate at which one quantity changes with respect to another. And them, we can compute the profit and loss of a process that a company or a system. Variety of optimization problems are solved by using derivatives. There were use derivatives to find the extreme values of functions, to determine and analyze the shape of graphs and to find numerically where a function equals zero. Kyi Sint | Kay Thi Win "Finding the Extreme Values with some Application of Derivatives" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29347.pdf Paper URL: https://www.ijtsrd.com/mathemetics/other/29347/finding-the-extreme-values-with-some-application-of-derivatives/kyi-sint
In classical data analysis, data are single values. This is the case if you consider a dataset of n patients which age and size you know. But what if you record the blood pressure or the weight of each patient during a day ? Then, for each patient, you do not have a single-valued data but a set of values since the blood pressure or the weight are not constant during the day.
Suppose now that you do not want to record blood pressure a thousand times for each patient and to store it into a database because your memory space is limited. Therefore, you need to aggregate each set of values into symbols: intervals (lower and upper bounds only), box plots, histograms or even distributions (distribution law with mean and variance)...
Thus, the issue is to adapt classical statistical tools to symbolic data analysis. More precisely, this article is aimed at proposing a method to fit a regression on Gaussian distributions. This paper is divided as follows: first, it presents the computation of the maximum likelihood estimator and then it compares the new approach with the usual least squares regression.
I am Vincent S. I am an Algorithm Assignment Expert at programminghomeworkhelp.com. I hold a Ph.D. in Programming from, University of Minnesota, USA. I have been helping students with their homework for the past 9 years. I solve assignments related to Algorithms.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Algorithm assignments.
Nec 602 unit ii Random Variables and Random processDr Naim R Kidwai
The presentation explains concept of Probability, random variable, statistical averages, correlation, sum of random Variables, Central Limit Theorem,
random process, classification of random processes, power spectral density, multiple random processes.
Motivated by presenting mathematics visually and interestingly to common people based on calculus and its extension, parametric curves are explored here to have two and three dimensional objects such that these objects can be used for demonstrating mathematics.
Epicycloid, hypocycloid are particular curves that are implemented in MATLAB programs and the motifs are presented here. The obtained curves are considered to be domains for complex mappings to have new variation of Figures and objects. Additionally Voronoi mapping is also implemented to some parametric curves and some resulting complex mappings.
Some obtained 3 dimensional objects are considered as flowers and animals inspiring to be mathematical ornaments of hypocycloid dance which is also illustrated here.
AACIMP 2010 Summer School lecture by Leonidas Sakalauskas. "Applied Mathematics" stream. "Stochastic Programming and Applications" course. Part 3.
More info at http://summerschool.ssa.org.ua
On New Root Finding Algorithms for Solving Nonlinear Transcendental EquationsAI Publications
In this paper, we present new iterative algorithms to find a root of the given nonlinear transcendental equations. In the proposed algorithms, we use nonlinear Taylor’s polynomial interpolation and a modified error correction term with a fixed-point concept. We also investigated for possible extension of the higher order iterative algorithms in single variable to higher dimension. Several numerical examples are presented to illustrate the proposed algorithms.
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.
Many functions in nature are described as the rate of change of another function. The concept is called the derivative. Algebraically, the process of finding the derivative involves a limit of difference quotients.
Continuity says that the limit of a function at a point equals the value of the function at that point, or, that small changes in the input give only small changes in output. This has important implications, such as the Intermediate Value Theorem.
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.
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.
Lesson 19: The Mean Value Theorem (Section 021 handout)Matthew Leingang
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.
Lesson 18: Maximum and Minimum Values (Section 041 slides)Matthew Leingang
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
Lesson 14: Derivatives of Exponential and Logarithmic Functions (Section 021 ...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.
Lesson 14: Derivatives of Exponential and Logarithmic Functions (Section 041 ...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.
Lesson 19: The Mean Value Theorem (Section 041 handout)Matthew Leingang
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.
Lesson 18: Maximum and Minimum Values (Section 041 handout)Matthew Leingang
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
Lesson 18: Maximum and Minimum Values (Section 021 slides)Matthew Leingang
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
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.
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 more good examples.
Lesson 18: Maximum and Minimum Values (Section 021 handout)Matthew Leingang
There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.
Lesson 14: Derivatives of Exponential and Logarithmic Functions (Section 041 ...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.
An antiderivative of a function is a function whose derivative is the given function. The problem of antidifferentiation is interesting, complicated, and useful, especially when discussing motion.
This is the handout version to take notes on.
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.
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
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.
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.
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 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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
1. Section 3.7
Indeterminate Forms and L’Hˆopital’s
Rule
V63.0121.021, Calculus I
New York University
November 4, 2010
Announcements
Quiz 3 in recitation this week on Sections 2.6, 2.8, 3.1, and 3.2
Announcements
Quiz 3 in recitation this
week on Sections 2.6, 2.8,
3.1, and 3.2
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 2 / 34
Objectives
Know when a limit is of
indeterminate form:
indeterminate quotients:
0/0, ∞/∞
indeterminate products:
0 × ∞
indeterminate differences:
∞ − ∞
indeterminate powers: 00
,
∞0
, and 1∞
Resolve limits in
indeterminate form
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 3 / 34
Notes
Notes
Notes
1
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
2. Experiments with funny limits
lim
x→0
sin2
x
x
= 0
lim
x→0
x
sin2
x
does not exist
lim
x→0
sin2
x
sin(x2)
= 1
lim
x→0
sin 3x
sin x
= 3
All of these are of the form
0
0
, and since we can get different answers in
different cases, we say this form is indeterminate.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 4 / 34
Recall
Recall the limit laws from Chapter 2.
Limit of a sum is the sum of the limits
Limit of a difference is the difference of the limits
Limit of a product is the product of the limits
Limit of a quotient is the quotient of the limits ... whoops! This is
true as long as you don’t try to divide by zero.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 5 / 34
More about dividing limits
We know dividing by zero is bad.
Most of the time, if an expression’s numerator approaches a finite
number and denominator approaches zero, the quotient approaches
some kind of infinity. For example:
lim
x→0+
1
x
= +∞ lim
x→0−
cos x
x3
= −∞
An exception would be something like
lim
x→∞
1
1
x sin x
= lim
x→∞
x csc x.
which does not exist and is not infinite.
Even less predictable: numerator and denominator both go to zero.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 6 / 34
Notes
Notes
Notes
2
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
3. Language Note
It depends on what the meaning of the word “is” is
Be careful with the language
here. We are not saying that
the limit in each case “is”
0
0
, and therefore nonexistent
because this expression is
undefined.
The limit is of the form
0
0
,
which means we cannot
evaluate it with our limit
laws.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 7 / 34
Indeterminate forms are like Tug Of War
Which side wins depends on which side is stronger.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 8 / 34
Outline
L’Hˆopital’s Rule
Relative Rates of Growth
Other Indeterminate Limits
Indeterminate Products
Indeterminate Differences
Indeterminate Powers
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 9 / 34
Notes
Notes
Notes
3
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
4. The Linear Case
Question
If f and g are lines and f (a) = g(a) = 0, what is
lim
x→a
f (x)
g(x)
?
Solution
The functions f and g can be written in the form
f (x) = m1(x − a)
g(x) = m2(x − a)
So
f (x)
g(x)
=
m1
m2
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 10 / 34
The Linear Case, Illustrated
x
y
y = f (x)
y = g(x)
a
x
f (x)
g(x)
f (x)
g(x)
=
f (x) − f (a)
g(x) − g(a)
=
(f (x) − f (a))/(x − a)
(g(x) − g(a))/(x − a)
=
m1
m2
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 11 / 34
What then?
But what if the functions aren’t linear?
Can we approximate a function near a point with a linear function?
What would be the slope of that linear function? The derivative!
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 12 / 34
Notes
Notes
Notes
4
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
5. Theorem of the Day
Theorem (L’Hopital’s Rule)
Suppose f and g are differentiable functions and g (x) = 0 near a (except
possibly at a). Suppose that
lim
x→a
f (x) = 0 and lim
x→a
g(x) = 0
or
lim
x→a
f (x) = ±∞ and lim
x→a
g(x) = ±∞
Then
lim
x→a
f (x)
g(x)
= lim
x→a
f (x)
g (x)
,
if the limit on the right-hand side is finite, ∞, or −∞.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 13 / 34
Meet the Mathematician: L’Hˆopital
wanted to be a military
man, but poor eyesight
forced him into math
did some math on his own
(solved the “brachistocrone
problem”)
paid a stipend to Johann
Bernoulli, who proved this
theorem and named it after
him! Guillaume Fran¸cois Antoine,
Marquis de L’Hˆopital
(French, 1661–1704)
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 14 / 34
Revisiting the previous examples
Example
lim
x→0
sin2
x
x
H
= lim
x→0
2 sin x
sin x → 0
cos x
1
= 0
Example
lim
x→0
sin2
x
numerator → 0
sin x2
denominator → 0
H
= lim
x→0
¡2 sin x cos x
numerator → 0
(cos x2) (¡2x
denominator → 0
)
H
= lim
x→0
cos2 x − sin2
x
numerator → 1
cos x2 − 2x2 sin(x2)
denominator → 1
= 1
Example
lim
x→0
sin 3x
sin x
H
= lim
x→0
3 cos 3x
cos x
= 3.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 15 / 34
Notes
Notes
Notes
5
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
6. Beware of Red Herrings
Example
Find
lim
x→0
x
cos x
Solution
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 16 / 34
Outline
L’Hˆopital’s Rule
Relative Rates of Growth
Other Indeterminate Limits
Indeterminate Products
Indeterminate Differences
Indeterminate Powers
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 17 / 34
Limits of Rational Functions revisited
Example
Find lim
x→∞
5x2 + 3x − 1
3x2 + 7x + 27
if it exists.
Solution
Using L’Hˆopital:
lim
x→∞
5x2 + 3x − 1
3x2 + 7x + 27
H
= lim
x→∞
10x + 3
6x + 7
H
= lim
x→∞
10
6
=
5
3
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 18 / 34
Notes
Notes
Notes
6
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
7. Limits of Rational Functions revisited II
Example
Find lim
x→∞
5x2 + 3x − 1
7x + 27
if it exists.
Solution
Using L’Hˆopital:
lim
x→∞
5x2 + 3x − 1
7x + 27
H
= lim
x→∞
10x + 3
7
= ∞
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 19 / 34
Limits of Rational Functions revisited III
Example
Find lim
x→∞
4x + 7
3x2 + 7x + 27
if it exists.
Solution
Using L’Hˆopital:
lim
x→∞
4x + 7
3x2 + 7x + 27
H
= lim
x→∞
4
6x + 7
= 0
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 20 / 34
Limits of Rational Functions
Fact
Let f (x) and g(x) be polynomials of degree p and q.
If p > q, then lim
x→∞
f (x)
g(x)
= ∞
If p < q, then lim
x→∞
f (x)
g(x)
= 0
If p = q, then lim
x→∞
f (x)
g(x)
is the ratio of the leading coefficients of f
and g.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 21 / 34
Notes
Notes
Notes
7
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
8. Exponential versus geometric growth
Example
Find lim
x→∞
ex
x2
, if it exists.
Solution
We have
lim
x→∞
ex
x2
H
= lim
x→∞
ex
2x
H
= lim
x→∞
ex
2
= ∞.
Example
What about lim
x→∞
ex
x3
?
Answer
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 22 / 34
Exponential versus fractional powers
Example
Find lim
x→∞
ex
√
x
, if it exists.
Solution (without L’Hˆopital)
We have for all x > 1, x1/2
< x1
, so
ex
x1/2
>
ex
x
The right hand side tends to ∞, so the left-hand side must, too.
Solution (with L’Hˆopital)
lim
x→∞
ex
√
x
= lim
x→∞
ex
1
2x−1/2
= lim
x→∞
2
√
xex
= ∞
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 23 / 34
Exponential versus any power
Theorem
Let r be any positive number. Then
lim
x→∞
ex
xr
= ∞.
Proof.
If r is a positive integer, then apply L’Hˆopital’s rule r times to the
fraction. You get
lim
x→∞
ex
xr
H
= . . .
H
= lim
x→∞
ex
r!
= ∞.
If r is not an integer, let m be the smallest integer greater than r. Then if
x > 1, xr
< xm
, so
ex
xr
>
ex
xm
. The right-hand side tends to ∞ by the
previous step.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 24 / 34
Notes
Notes
Notes
8
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
9. Any exponential versus any power
Theorem
Let a > 1 and r > 0. Then
lim
x→∞
ax
xr
= ∞.
Proof.
If r is a positive integer, we have
lim
x→∞
ax
xr
H
= . . .
H
= lim
x→∞
(ln a)r ax
r!
= ∞.
If r isn’t an integer, we can compare it as before.
So even lim
x→∞
(1.00000001)x
x100000000
= ∞!
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 25 / 34
Logarithmic versus power growth
Theorem
Let r be any positive number. Then
lim
x→∞
ln x
xr
= 0.
Proof.
One application of L’Hˆopital’s Rule here suffices:
lim
x→∞
ln x
xr
H
= lim
x→∞
1/x
rxr−1
= lim
x→∞
1
rxr
= 0.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 26 / 34
Outline
L’Hˆopital’s Rule
Relative Rates of Growth
Other Indeterminate Limits
Indeterminate Products
Indeterminate Differences
Indeterminate Powers
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 27 / 34
Notes
Notes
Notes
9
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
10. Indeterminate products
Example
Find
lim
x→0+
√
x ln x
This limit is of the form 0 · (−∞).
Solution
Jury-rig the expression to make an indeterminate quotient. Then apply
L’Hˆopital’s Rule:
lim
x→0+
√
x ln x = lim
x→0+
ln x
1/
√
x
H
= lim
x→0+
x−1
−1
2x−3/2
= lim
x→0+
−2
√
x = 0
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 28 / 34
Indeterminate differences
Example
lim
x→0+
1
x
− cot 2x
This limit is of the form ∞ − ∞.
Solution
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 29 / 34
Indeterminate powers
Example
Find lim
x→0+
(1 − 2x)1/x
Take the logarithm:
ln lim
x→0+
(1 − 2x)1/x
= lim
x→0+
ln (1 − 2x)1/x
= lim
x→0+
ln(1 − 2x)
x
This limit is of the form
0
0
, so we can use L’Hˆopital:
lim
x→0+
ln(1 − 2x)
x
H
= lim
x→0+
−2
1−2x
1
= −2
This is not the answer, it’s the log of the answer! So the answer we want
is e−2
.
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 31 / 34
Notes
Notes
Notes
10
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010
11. Another indeterminate power limit
Example
lim
x→0
(3x)4x
Solution
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 32 / 34
Summary
Form Method
0
0 L’Hˆopital’s rule directly
∞
∞ L’Hˆopital’s rule directly
0 · ∞ jiggle to make 0
0 or ∞
∞ .
∞ − ∞ combine to make an indeterminate product or quotient
00 take ln to make an indeterminate product
∞0 ditto
1∞ ditto
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 33 / 34
Final Thoughts
L’Hˆopital’s Rule only works on indeterminate quotients
Luckily, most indeterminate limits can be transformed into
indeterminate quotients
L’Hˆopital’s Rule gives wrong answers for non-indeterminate limits!
V63.0121.021, Calculus I (NYU) Section 3.7 L’Hˆopital’s Rule November 4, 2010 34 / 34
Notes
Notes
Notes
11
Section 3.7 : L’Hˆopital’s RuleV63.0121.021, Calculus I November 4, 2010