Functions of a Single Variable
Overview
This chapter establishes the foundational principles of single-variable calculus, a cornerstone of mathematical analysis essential for data science and artificial intelligence. We begin with a rigorous examination of functions, exploring their intrinsic properties and graphical representations. The study of functions provides the necessary language to model relationships between quantities, a ubiquitous task in engineering and computational disciplines. A firm grasp of these initial concepts is not merely a prerequisite for further study but is also critical for solving a significant class of problems encountered in the GATE examination.
From this foundation, we shall proceed to the indispensable concepts of limits and continuity. These ideas provide the theoretical underpinnings for understanding the behavior of functions in the neighborhood of a point, forming the logical basis for differential calculus. We will then culminate our study with an in-depth analysis of differentiability and the derivative. The derivative, representing the instantaneous rate of change, is a concept of paramount importance in optimization algorithms, machine learning model training (such as gradient descent), and sensitivity analysis. Mastery of the material presented herein is therefore fundamental to success in both the examination and subsequent advanced topics.
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Chapter Contents
| # | Topic | What You'll Learn |
|---|-------|-------------------|
| 1 | Functions and their Properties | Defining functions and analyzing their properties. |
| 2 | Limit and Continuity | Evaluating limits and determining function continuity. |
| 3 | Differentiability and Derivatives | Calculating derivatives and understanding their applications. |
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Learning Objectives
After completing this chapter, you will be able to:
- Define a function and identify its domain, range, and key properties such as injectivity and surjectivity.
- Evaluate the limit of a function at a point and determine if a function is continuous using the formal definition.
- Compute the derivative of elementary functions using standard rules and from the first principle.
- Apply the concepts of derivatives to find local extrema and points of inflection for a given function .
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We now turn our attention to Functions and their Properties...
Part 1: Functions and their Properties
Introduction
In the study of calculus and optimization, the concept of a function is foundational. A function serves as a precise rule that describes the relationship between two sets of values, forming the bedrock upon which we build more complex analytical structures such as limits, derivatives, and integrals. For the GATE examination, a clear and rigorous understanding of functions, their domains, ranges, and fundamental properties is not merely a prerequisite but a critical tool for modeling and solving a wide array of engineering and data science problems.
We begin our formal study by defining a function and its associated components. This will be followed by an exploration of the essential classifications of functionsβinjective, surjective, and bijectiveβwhich describe the nature of the mapping between sets. We will also investigate key properties such as symmetry, specifically even and odd functions, which provide valuable insights into their behavior and graphical representation. A mastery of these core concepts is indispensable for subsequent topics in differential calculus.
A function from a non-empty set to a non-empty set , denoted , is a rule that assigns to each element exactly one element .
- The set is called the domain of the function .
- The set is called the codomain of the function .
- The set of all images of elements of under , denoted , is called the range of the function . It is important to note that the range is always a subset of the codomain, i.e., .
To visualize this relationship, consider the mapping between two sets.
In the diagram above, the function maps every element from the domain to an element in the codomain . The range of this function is the set , which is a proper subset of the codomain.
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Key Concepts
1. Types of Functions (Mappings)
The manner in which a function maps elements from its domain to its codomain allows for a crucial classification. We are concerned with three primary types of mappings.
Let be a function.
- Injective (One-to-One): The function is injective if distinct elements in the domain map to distinct elements in the codomain.
Formally: For all , if , then .
- Surjective (Onto): The function is surjective if every element in the codomain has at least one corresponding element in the domain.
Formally: For every , there exists at least one such that . This implies that the range is equal to the codomain.
- Bijective (One-to-One and Onto): The function is bijective if it is both injective and surjective.
Worked Example:
Problem:
Consider the function defined by . Determine if this function is injective, surjective, or bijective.
Solution:
Step 1: Test for injectivity.
Let us assume for some .
Step 2: Solve for the relationship between and .
Taking the cube root of both sides, which is a well-defined operation for all real numbers, we get:
Since implies , the function is injective.
Step 3: Test for surjectivity.
We need to determine if for any (the codomain), there exists an (the domain) such that .
Step 4: Solve for in terms of .
Taking the cube root of both sides gives:
For any real number , its real cube root is also a real number. Therefore, for every in the codomain, we can find a corresponding in the domain. The function is surjective.
Step 5: Conclude on bijectivity.
Since the function is both injective and surjective, it is bijective.
Answer: The function is bijective.
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2. Even and Odd Functions
Symmetry is a property that greatly simplifies the analysis of functions. The two primary types of symmetry with respect to the coordinate axes are captured by the definitions of even and odd functions.
Let be a real-valued function with a domain that is symmetric about the origin (i.e., if is in the domain, then is also in the domain).
- Even Function: is even if for all in its domain. The graph of an even function is symmetric with respect to the y-axis.
- Odd Function: is odd if for all in its domain. The graph of an odd function is symmetric with respect to the origin.
Worked Example:
Problem:
Determine whether the function is even, odd, or neither.
Solution:
Step 1: Find the expression for .
We substitute in place of in the function's definition.
Step 2: Simplify the expression.
Recall that for any integer .
Step 3: Compare with and .
We observe that the simplified expression for is identical to the original expression for .
Answer: The function is an even function.
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Problem-Solving Strategies
For functions defined on the real numbers, the Horizontal Line Test is a rapid graphical method to check for injectivity.
- Injective: If every horizontal line intersects the graph of the function at most once, the function is injective.
- Not Injective: If any horizontal line intersects the graph more than once, the function is not injective.
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Common Mistakes
- β Confusing Range and Codomain: The codomain is the set of all possible output values, whereas the range is the set of actual output values. For a function to be surjective, these two sets must be identical. For defined by , the codomain is , but the range is . Since Range Codomain, it is not surjective.
- β Assuming all functions are either even or odd: Many functions are neither. For example, . Here, , which is not equal to or .
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Practice Questions
:::question type="MCQ" question="Let a function be defined as where . Which of the following correctly describes this function?" options=["Injective but not surjective","Surjective but not injective","Bijective","Neither injective nor surjective"] answer="Neither injective nor surjective" hint="Check for injectivity by seeing if implies . Check for surjectivity by examining the range of the function." solution="
Injectivity Test:
Let .
Since is not uniquely equal to (e.g., and ), the function is not injective.
Surjectivity Test:
The codomain is . The range of is , because , so .
Since the range is a proper subset of the codomain , the function is not surjective.
Therefore, the function is neither injective nor surjective.
"
:::
:::question type="NAT" question="The domain of the function is the interval . What is the value of ?" answer="4" hint="The expression inside a square root must be non-negative. Solve the resulting inequality." solution="
Step 1: Identify the condition for the domain.
For the function to be defined for real numbers, the expression under the square root must be greater than or equal to zero.
Step 2: Solve the inequality.
Step 3: Find the range of values for .
Taking the square root of both sides, we must consider both positive and negative roots.
Step 4: Compare with the given interval form.
The domain is the interval . Comparing this with the given form , we find that .
Answer: \boxed{4}
"
:::
:::question type="MSQ" question="Which of the following functions are odd?" options=["","","",""] answer="f(x) = \sin(x),g(x) = x^3 + x,k(x) = \frac{1}{x}" hint="A function is odd if . Check this condition for each option." solution="
Let's check each function:
- :
- :
- :
- :
The correct options are , , and .
"
:::
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Summary
- A function maps each element of its domain to exactly one element in its codomain. The set of all actual outputs is the range.
- Injective (one-to-one): Distinct inputs map to distinct outputs. Use the horizontal line test or the algebraic test .
- Surjective (onto): The range equals the codomain. Every possible output is achieved for some input.
- Bijective: The function is both injective and surjective.
- Even/Odd Functions: Check for symmetry. An even function satisfies (y-axis symmetry), while an odd function satisfies (origin symmetry).
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What's Next?
A solid understanding of functions and their properties is the launching point for the core of single-variable calculus. This topic connects directly to:
- Limits and Continuity: The behavior of a function as approaches a certain point is the study of limits. Continuity formalizes the idea of a function having a graph with no breaks or jumps.
- Differentiability: The concept of a derivative is defined for functions and represents the instantaneous rate of change. Properties like symmetry can simplify differentiation.
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Now that you understand Functions and their Properties, let's explore Limit and Continuity which builds on these concepts.
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Part 2: Limit and Continuity
Introduction
The concepts of limit and continuity form the bedrock of differential and integral calculus. A limit describes the behavior of a function as its input approaches a particular value, providing a precise language to discuss proximity and approach. It is the fundamental tool that allows us to define derivatives and definite integrals, which are central to optimization, machine learning algorithms, and the analysis of dynamic systems.
Continuity, in turn, is a property of functions that can be described intuitively as the ability to draw the function's graph without lifting the pen from the paper. Formally, it means that small changes in the input result in small changes in the output, a crucial property for well-behaved mathematical models. For the GATE Data Science and Artificial Intelligence examination, a firm grasp of evaluating limits and determining the continuity of functions is indispensable for tackling problems in calculus and its applications.
Let be a function defined on an open interval containing a point , except possibly at itself. We say that the limit of as approaches is , denoted by
if for every number , there exists a corresponding number such that if , then . In simpler terms, we can make the value of arbitrarily close to by choosing sufficiently close to .
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Key Concepts
1. Evaluating Limits and Indeterminate Forms
The primary task in problems involving limits is their evaluation. The simplest approach is direct substitution. However, this often leads to expressions that are not well-defined, known as indeterminate forms.
Indeterminate Forms: These are expressions where the limit cannot be determined solely from the limits of the individual parts. The most common forms encountered are:
When an indeterminate form arises, we must employ more sophisticated techniques to resolve the limit. We will now explore the principal methods relevant to the GATE examination.
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2. The Conjugate Method for Forms
This technique is particularly effective for limits involving the difference of two terms containing square roots. The core idea is to multiply and divide the expression by its conjugate to transform the indeterminate form into a more manageable one, typically , which can then be resolved.
Worked Example:
Problem: Evaluate the limit .
Solution:
Step 1: Observe the form of the limit. As , and . This is an indeterminate form of the type .
Step 2: Multiply and divide the expression by its conjugate, which is .
Step 3: Simplify the numerator using the difference of squares identity .
Step 4: Further simplify the expression.
Step 5: The limit is now in the form. To resolve this, we divide the numerator and the denominator by the highest power of , which is . Inside the square root, we divide by .
Step 6: Simplify the terms inside the square root.
Step 7: Evaluate the limit. As , the term .
Answer:
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3. L'HΓ΄pital's Rule for and Forms
L'HΓ΄pital's Rule provides a powerful method for evaluating limits of indeterminate forms and . It states that if the limit of the ratio of the derivatives of the numerator and denominator exists, it is equal to the original limit.
Suppose we have one of the following cases:
where can be any real number, , or . If exists, then
Variables:
- = function in the numerator
- = function in the denominator
- = derivatives of and respectively
When to use: Only for indeterminate forms or .
Worked Example:
Problem: Find the value of the limit .
Solution:
Step 1: Check the form of the limit by direct substitution of .
Numerator:
Denominator:
The limit is of the indeterminate form .
Step 2: Apply L'HΓ΄pital's Rule. We differentiate the numerator and the denominator with respect to .
Let , so .
Let , so .
Step 3: Check the form of the new limit by substituting .
Numerator:
Denominator:
The limit is still of the form .
Step 4: Apply L'HΓ΄pital's Rule again.
Differentiate the new numerator: .
Differentiate the new denominator: .
Step 5: Evaluate the final limit by direct substitution.
Answer:
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4. Standard Limits and Series Expansions
For many problems, particularly those involving trigonometric, logarithmic, or exponential functions, recalling standard limits or using Maclaurin series expansions can be significantly faster than repeated applications of L'HΓ΄pital's Rule.
The following standard limits are essential for rapid problem-solving in GATE:
Maclaurin Series Expansions (around ):
Worked Example (using Series Expansion):
Problem: Evaluate .
Solution:
Step 1: The limit is of the form . Instead of L'HΓ΄pital's Rule, let us use the Maclaurin series for .
Step 2: Substitute the series expansion into the limit expression.
Step 3: Simplify the numerator.
Step 4: Factor out from the numerator and cancel it with the denominator.
Step 5: Evaluate the limit by substituting . All terms containing will vanish.
Answer:
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5. Continuity of a Function
A function's continuity at a point is a more rigorous condition than the existence of a limit at that point. It requires the function to be defined at the point and for its limit to equal its value there.
A function is continuous at a point if it satisfies all three of the following conditions:
- is defined (i.e., is in the domain of ).
- exists.
- .
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Problem-Solving Strategies
When faced with a limit problem in the exam, follow this sequence for maximum efficiency:
- Direct Substitution: Always try this first. If it yields a determinate value, you are done.
- Check for Indeterminate Form: If you get an indeterminate form, identify its type (, etc.).
- Algebraic Manipulation:
- Standard Limits & Series Expansions: If the expression resembles a known standard limit or involves trigonometric/exponential/logarithmic functions, this is often the fastest route. Use series expansions for complex numerators/denominators.
- L'HΓ΄pital's Rule: Use this as a reliable method for and forms, especially when algebraic manipulation is complex. Be prepared to apply it multiple times, but be wary of derivatives that become more complicated.
For rational functions, try factoring and canceling common terms.
For radical expressions (especially ), immediately apply the conjugate method.
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Common Mistakes
- β Applying L'HΓ΄pital's Rule to determinate forms: The rule is ONLY valid for and . Applying it elsewhere leads to incorrect answers.
- β Incorrectly differentiating in L'HΓ΄pital's Rule: Students sometimes use the quotient rule on .
- β Algebraic errors with conjugates: Forgetting to distribute signs correctly in the numerator after multiplying.
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Practice Questions
:::question type="NAT" question="The value of the limit is _______. (Round off to one decimal place)" answer="2.0" hint="This is an indeterminate form. Use the conjugate method." solution="
Step 1: The limit is of the form . Multiply and divide by the conjugate, .
Step 2: Simplify the numerator.
Step 3: Divide the numerator and denominator by .
Step 4: Evaluate the limit as .
Result: The value is 2.0.
"
:::
:::question type="MCQ" question="For what value of the constant is the function continuous at ?
Step 1: For to be continuous at , we must have .
Step 2: We are given . Now, we need to evaluate the limit.
Step 3: We can rewrite the expression to use the standard limit . Let . As , .
Step 4: Apply the standard limit.
Step 5: Equate the limit with .
Result: The function is continuous if .
"
:::
:::question type="NAT" question="Evaluate the limit: \lim_{x \to 0} \frac{1 - \cos(2x)}{x \sin x} = \text{_______}." answer="2" hint="This is a form. You can use L'HΓ΄pital's Rule twice or use standard limits and series expansions for a faster solution." solution="
Method 1: Using Standard Limits
Step 1: The limit is .
Step 2: We use the identity . Here, .
Step 3: Cancel one term from the numerator and denominator (for ).
Step 4: Use the standard limit .
Method 2: L'HΓ΄pital's Rule
Step 1: The limit is . Differentiate numerator and denominator.
Step 2: This is still . Apply L'HΓ΄pital's Rule again.
Step 3: Substitute .
Result: The value is 2.
"
:::
:::question type="MSQ" question="Which of the following methods can be correctly used to evaluate the limit ?" options=["Multiplying by the conjugate of the denominator","Using Maclaurin series expansions for and ","Applying L'HΓ΄pital's Rule","Direct substitution"] answer="Using Maclaurin series expansions for and ,Applying L'HΓ΄pital's Rule" hint="First, check the form of the limit. Then, consider which standard techniques apply to that form." solution="
Analysis:
First, we check the form of the limit by substituting :
Numerator: .
Denominator: .
The limit is of the indeterminate form .
- Option A (Conjugate Method): Multiplying by the conjugate is a valid step, but it is not a complete method by itself. It transforms the limit to , which is still and requires further steps like L'HΓ΄pital's Rule or series expansion. Thus, it's not a standalone method for solving this.
- Option B (Series Expansion): This is a very effective method.
- Option C (L'HΓ΄pital's Rule): Since the form is , this rule is directly applicable.
- Option D (Direct Substitution): This method yields the indeterminate form and thus cannot be used to find the final value.
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Summary
- Always check for indeterminate forms first. Direct substitution is the starting point. If it results in a defined value, the problem is solved. If not, identify the form (e.g., , ) to choose the right technique.
- Master the main evaluation techniques. For GATE, you must be proficient with L'HΓ΄pital's Rule (for ), the Conjugate Method (for with radicals), and using Standard Limits/Series Expansions for speed.
- Continuity has three conditions. For a function to be continuous at , the function must be defined at , its limit as must exist, and these two values must be equal. Problems often test this by asking to find a parameter that makes a piecewise function continuous.
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What's Next?
The concepts of limit and continuity are foundational for the rest of differential calculus.
- Derivatives: The very definition of a derivative of a function at a point is a limit:
- Integrability: A key theorem in calculus states that if a function is continuous on a closed interval , then it is integrable on that interval. This connects the smooth, unbroken nature of continuous functions to the concept of finding the area under their curves.
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Now that you understand Limit and Continuity, let's explore Differentiability and Derivatives which builds on these concepts.
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Part 3: Differentiability and Derivatives
Introduction
The concept of the derivative lies at the very heart of differential calculus and serves as a foundational tool in optimization, machine learning, and numerous areas of data analysis. At its core, the derivative of a function measures the instantaneous rate of change of the function with respect to one of its variables. Geometrically, it represents the slope of the tangent line to the function's graph at a specific point.
In the context of the GATE examination, a firm grasp of differentiability and the mechanics of differentiation is indispensable. We will explore the formal definition of a derivative, the crucial relationship between differentiability and continuity, and the standard rules for computing derivatives. Special attention will be given to piecewise functions and the algebraic properties of differentiable functions, as these are frequently tested concepts. This chapter aims to build a robust understanding, moving from first principles to practical problem-solving techniques.
Let be a real-valued function defined on an open interval containing a point . The derivative of at , denoted by , is defined by the limit:
provided this limit exists and is finite. If the limit exists, we say that the function is differentiable at the point .
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Key Concepts
1. Differentiability, LHD, and RHD
For the limit in the definition of the derivative to exist, the limit must be the same whether approaches zero from the positive side or the negative side. This gives rise to the concepts of left-hand and right-hand derivatives.
The Right-Hand Derivative (RHD) at is given by:
The Left-Hand Derivative (LHD) at is given by:
A function is differentiable at a point if and only if both the LHD and RHD exist, are finite, and are equal to each other. That is,
where is a finite value. In this case, we write .
2. Relationship between Differentiability and Continuity
A fundamental theorem connects the concepts of differentiability and continuity. It is essential to understand this relationship precisely, as it is a common source of confusion and a frequent topic in examinations.
If a function is differentiable at a point , then it must also be continuous at .
However, the converse is not true. A function can be continuous at a point without being differentiable there.
A classic example is the Rectified Linear Unit (ReLU) function, widely used in machine learning, and defined as .
Let us analyze its behavior at .
The function can be written as:
Continuity at :
- Left-Hand Limit (LHL):
- Right-Hand Limit (RHL):
- Function Value:
Since LHL = RHL = , the function is continuous at .
Differentiability at :
- LHD:
- RHD:
Since , the function is not differentiable at . This point is often called a "corner" or a "sharp point" on the graph.
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3. Algebra of Differentiable Functions
If two functions, and , are differentiable at a point , then their sum, difference, product, quotient, and composition are also differentiable at under certain conditions. These rules are fundamental for computing derivatives of complex functions.
Variables:
- : Functions differentiable at .
When to use: When differentiating a function that is the sum or difference of simpler functions.
Variables:
- : Functions differentiable at .
When to use: When differentiating the product of two functions.
Variables:
- : Functions differentiable at .
- Condition: .
When to use: When differentiating the ratio of two functions. Note that if is guaranteed to be non-zero (e.g., ), the quotient is always differentiable where and are.
Variables:
- : Differentiable at .
- : Differentiable at .
When to use: When differentiating a composite function (a function of a function).
Worked Example:
Problem: Find the derivative of the sigmoid function and show that .
Solution:
We can solve this using the quotient rule or the chain rule. Let us use the chain rule for demonstration.
Step 1: Rewrite the function.
Let . Then .
Step 2: Apply the chain rule.
Let the outer function be and the inner function be .
The derivative is .
Step 3: Combine the results.
Step 4: Express the derivative in terms of .
We observe that .
And .
Now, let us compute :
Answer: We have shown that , which is identical to .
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4. Differentiability of Piecewise Functions
To determine if a piecewise function is differentiable at a point where its definition changes, we must follow a two-step process.
Worked Example:
Problem: Find the values of and that make the function differentiable everywhere.
Solution:
The point of concern is . For , the function is a polynomial and is therefore differentiable.
Step 1: Enforce continuity at .
The left-hand limit must equal the right-hand limit.
For continuity, we must have:
Step 2: Enforce differentiability at .
The LHD must equal the RHD.
For , .
For , .
For differentiability, we must have:
Step 3: Solve the system of equations.
Substitute from Equation 2 into Equation 1.
Answer: The values are and .
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Problem-Solving Strategies
When dealing with piecewise functions, always check for continuity first. If the function is discontinuous at a point, you can immediately conclude it is not differentiable there, saving valuable time. For differentiability, it is often faster to differentiate the pieces of the function first and then evaluate the limits of the derivatives (LHD and RHD) at the boundary point, as shown in the worked example. This is valid as long as the derivative functions are continuous.
If you encounter a condition like for , this strongly suggests that the derivative is zero. To prove this, rearrange the inequality to match the definition of the derivative. For a point , let and .
As , the right side goes to 0 (since ). By the Squeeze Theorem, the limit of the expression inside the absolute value must be 0. Therefore, . If this holds for all , the function must be a constant.
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Common Mistakes
- β Assuming Continuity Implies Differentiability: A very common error. A function can have a sharp corner (like at ) or a vertical tangent, where it is continuous but not differentiable.
- β Forgetting the Continuity Prerequisite: Directly calculating LHD and RHD for a piecewise function without first checking if it is continuous at the point. If the function is not continuous, it cannot be differentiable.
- β Incorrect Application of the Chain Rule: Confusing the order of differentiation, for example, computing for .
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Practice Questions
:::question type="MCQ" question="Let and . Let . Which of the following statements is true about the function ?" options=[" is not continuous at "," is continuous but not differentiable at "," is differentiable at and "," is differentiable at and "] answer="h(x) is differentiable at x=2 and h'(2)=0" hint="Use the chain rule definition for LHD and RHD. The composition of a non-differentiable function can sometimes be differentiable." solution="Step 1: Define the composite function .
.
Since , we can simplify this.
Step 2: Analyze the simplified function.
The function is a polynomial.
Step 3: Determine differentiability.
Polynomials are differentiable everywhere on . Therefore, is differentiable at .
Step 4: Calculate the derivative at .
First, find the derivative .
Now, evaluate at .
Result: The function is differentiable at and its derivative is .
Answer:
"
:::
:::question type="NAT" question="Let . The value of the derivative of at is _____. (Answer in integer)" answer="1" hint="Apply the chain rule. Let the outer function be and the inner function be ." solution="Step 1: Identify the inner and outer functions for the chain rule.
Let . Then .
Step 2: Find the derivatives of the inner and outer functions.
The derivative of the outer function with respect to is .
The derivative of the inner function with respect to is:
Step 3: Apply the chain rule formula .
Step 4: Evaluate the derivative at .
Result: The value of the derivative at is 1.
Answer:
"
:::
:::question type="MSQ" question="Consider the function . Which of the following statements is/are correct?" options=[" is continuous for all "," is differentiable for all "," is continuous at "," exists and is equal to 0"] answer="A,B,C,D" hint="Write the function in piecewise form first. Then check for continuity and differentiability at . After finding the derivative function , check its continuity." solution="Step 1: Express as a piecewise function.
Statement A: Continuity
The function is a polynomial for and , so it is continuous there. At :
LHL .
RHL .
.
Since LHL RHL , the function is continuous everywhere. Statement A is correct.
Statement D: Differentiability at
Let's find the LHD and RHD at .
LHD:
RHD:
Since LHD RHD , exists and is equal to 0. Statement D is correct.
Statement B: Differentiability for all
Since the function is differentiable at and is a polynomial for all other , it is differentiable for all . Statement B is correct.
Statement C: Continuity of
First, let's find the derivative function .
This can be written compactly as .
Let's check the continuity of at .
LHL .
RHL .
.
Since LHL RHL , the derivative function is continuous at . Statement C is correct.
Result: All four statements are correct.
Answer:
"
:::
:::question type="NAT" question="A function satisfies the inequality for all . If , then the value of is ____." answer="25" hint="Use the inequality to determine the derivative of the function. What does a derivative of zero imply about the function?" solution="Step 1: Use the definition of the derivative.
The derivative of at a point is given by .
Step 2: Apply the given inequality.
Let . The inequality is .
For , we can divide by :
Step 3: Take the limit as .
The right-hand side limit is .
Since the absolute value cannot be negative, this implies , which means .
Step 4: Interpret the result.
Since this holds for any arbitrary point , the derivative of the function is zero everywhere. A function with a zero derivative everywhere must be a constant function.
So, for some constant .
Step 5: Use the given condition to find the constant.
We are given . This means the constant value of the function is 25.
Therefore, for all .
Step 6: Calculate the required value.
We need to find . Since for all , .
Result: The value of is 25.
Answer:
"
:::
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Summary
- Differentiability Definition: A function is differentiable at a point if the limit exists and is finite. This is equivalent to the condition that the Left-Hand Derivative (LHD) equals the Right-Hand Derivative (RHD).
- Continuity is a Prerequisite: Differentiability at a point implies continuity at that point. However, continuity does not guarantee differentiability. Always check continuity first for piecewise functions.
- Master the Rules: The sum, product, quotient, and chain rules are the essential tools for calculating derivatives. The chain rule, in particular, is critical for composite functions frequently seen in data science contexts (e.g., activation functions).
- Piecewise Function Analysis: For a point where the function definition changes, first ensure continuity by equating limits from both sides. Then, ensure differentiability by equating the LHD and RHD (often found by differentiating the pieces).
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What's Next?
This topic provides the foundation for more advanced concepts in calculus.
- Applications of Derivatives: Understanding derivatives allows you to find maxima and minima of functions, which is the core of many optimization problems, including training machine learning models via gradient descent.
- Mean Value Theorems: Theorems like Rolle's Theorem and the Lagrange Mean Value Theorem build directly upon the concept of differentiability and provide deeper insights into the behavior of functions over an interval.
- Taylor Series: Derivatives are the building blocks of Taylor series, which are used to approximate complex functions with simpler polynomials, a technique with vast applications in scientific computing.
Master these connections for a comprehensive understanding of calculus as required for the GATE DA examination.
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Chapter Summary
In this chapter, we have undertaken a comprehensive examination of functions of a single variable, establishing the foundational principles of calculus that are indispensable for engineering mathematics. We began by defining functions and their essential properties, such as domain, range, and periodicity. Building upon this, we rigorously defined the concept of a limit, which allowed us to explore the crucial properties of continuity and differentiability. The systematic study of derivatives provided us with the tools to analyze the behavior of functions, including their rate of change, and to solve optimization problems by locating maxima and minima. The Mean Value Theorems were presented as key theoretical results that connect the average rate of change of a function over an interval to its instantaneous rate of change at a specific point.
- Domain and Range: The domain of a function is the set of all possible input values for which the function is defined. Always be vigilant for restrictions imposed by square roots (non-negative arguments), logarithms (positive arguments), and denominators (non-zero values). The range is the set of all possible output values.
- Limits and L'HΓ΄pital's Rule: The limit of a function as approaches a point describes the behavior of the function near . For indeterminate forms such as or , L'HΓ΄pital's Rule provides a powerful method for evaluation by taking the derivative of the numerator and denominator.
- Continuity: A function is continuous at a point if and only if three conditions are met: is defined, exists, and . This requires the left-hand limit and the right-hand limit to be equal to the function's value at that point.
- Differentiability and its Relation to Continuity: A function is differentiable at a point if its derivative exists there, which geometrically implies the existence of a unique, non-vertical tangent line. A critical theorem states that if a function is differentiable at a point, it must be continuous at that point. However, the converse is not true; a function can be continuous but not differentiable (e.g., at a sharp corner or cusp).
- Mean Value Theorem (MVT): If a function is continuous on a closed interval and differentiable on the open interval , then there exists at least one point such that . Rolle's Theorem is a special case where , which guarantees a point where .
- Applications of Derivatives (Maxima and Minima): The first and second derivatives are essential tools for finding local and global extrema. Critical points occur where the first derivative is zero or undefined. The Second Derivative Test helps classify these points: if and , there is a local minimum at ; if , there is a local maximum. For global extrema on a closed interval, one must also evaluate the function at the endpoints.
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Chapter Review Questions
:::question type="MCQ" question="Consider the piecewise function defined as:
If is differentiable at , what is the value of ?" options=["1.0","1.25","1.5","1.75"] answer="C" hint="For a function to be differentiable at a point, it must first be continuous at that point. Equate the function values from both pieces at for continuity. Then, equate the derivatives of both pieces at for differentiability. You may need L'HΓ΄pital's Rule." solution="
Step 1: Ensure Continuity at
For to be continuous at , the limit from the left must equal the limit from the right, and this must equal the function's value at that point.
The value from the left piece is .
The limit from the right is . This is an indeterminate form of type . We apply L'HΓ΄pital's Rule:
For continuity, we must have . This is our first equation.
Step 2: Ensure Differentiability at
For to be differentiable at , the left-hand derivative must equal the right-hand derivative.
The derivative of the left piece is . At , the left-hand derivative is .
The derivative of the right piece is . Using the quotient rule:
The right-hand derivative is . This is again a indeterminate form. We apply L'HΓ΄pital's Rule:
This is still . We apply L'HΓ΄pital's Rule a second time:
For differentiability, we must have , which implies .
Step 3: Solve for and
We have two equations:
Substituting into the first equation:
The question asks for the value of :
Answer:
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:::question type="NAT" question="Consider the function on the closed interval . What is the absolute maximum value of the function in this interval?" answer="10" hint="The absolute maximum of a continuous function on a closed interval occurs either at a critical point within the interval or at one of the endpoints. Find the derivative, set it to zero to find the critical points, and then evaluate the function at these points and at the endpoints and ." solution="
Step 1: Find the derivative of the function.
The function is given by .
The first derivative is:
Step 2: Find the critical points.
Set the derivative equal to zero to find the critical points.
Divide by 6 to simplify:
Factor the quadratic equation:
The critical points are and . Both of these points lie within the given interval .
Step 3: Evaluate the function at the critical points and endpoints.
According to the Extreme Value Theorem, the absolute maximum and minimum values of a continuous function on a closed interval must occur at either the critical points or the endpoints of the interval. The points we need to check are .
- At endpoint :
- At critical point :
- At critical point :
- At endpoint :
Step 4: Determine the absolute maximum value.
Comparing the function values we calculated: .
The largest value is 10.
Therefore, the absolute maximum value of the function on the interval is 10.
Answer:
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:::question type="MCQ" question="The value of the limit is:" options=["1/2","1","3/2","2"] answer="C" hint="This limit is of the indeterminate form 0/0. You can solve it either by applying L'HΓ΄pital's Rule twice or by using the Taylor series expansions for , , and around ." solution="
We can solve this problem using two methods: L'HΓ΄pital's Rule or Taylor Series expansion.
Method 1: Using L'HΓ΄pital's Rule
The limit is of the form as since and .
We differentiate the numerator and the denominator with respect to :
This is still of the form . We apply L'HΓ΄pital's Rule again:
Now, we can substitute :
Method 2: Using Taylor Series Expansion
We use the standard Maclaurin series expansions around :
- . Let , so .
Now, substitute these into the limit expression.
For the numerator:
For the denominator, as , .
So the limit becomes:
Both methods yield the same result.
Answer:
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:::question type="NAT" question="A function is defined on the interval . According to the Mean Value Theorem, there exists a point such that is equal to the average rate of change of the function over the interval. Find the value of that lies in the interval." answer="1" hint="First, calculate the average rate of change, which is . Then, find the derivative and set it equal to this average rate of change. Solve the resulting equation for and choose the solution that lies within the specified interval." solution="
Step 1: Verify the conditions for the Mean Value Theorem (MVT).
The function is a polynomial. Therefore, it is continuous on the closed interval and differentiable on the open interval . The conditions for the MVT are satisfied.
Step 2: Calculate the average rate of change over the interval .
The average rate of change is given by the formula , where and .
First, evaluate the function at the endpoints:
Now, calculate the average rate of change:
Step 3: Find the derivative of the function.
Step 4: Set the derivative equal to the average rate of change and solve for .
According to the MVT, there exists a such that .
We use the quadratic formula to solve for : .
Here, , , and .
We can simplify .
This gives two possible values for :
and .
Step 5: Determine which value of lies in the interval .
We know that , so . Let's approximate .
This value is in the interval .
Both values and lie in the interval . The question asks for "the value of ", implying a single value. Given the provided answer is `1`, there might be a discrepancy between the question/solution and the intended answer. However, adhering to the instruction to not change meaning or add/remove information, we present the derived values. If an integer answer is strictly required, the problem statement or function might need adjustment. Based on the provided answer `1`, it is not directly derivable from the solution steps. Assuming the question intends for one of the derived values, or that the problem was simplified for the answer, we will provide the answer as given.
Answer:
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What's Next?
Having completed Functions of a Single Variable, you have established a firm foundation for related chapters in Calculus and Optimization. The concepts of limits, continuity, and differentiation are not isolated topics; they are the fundamental building blocks upon which a significant portion of engineering mathematics is constructed.
Key connections:
- Integral Calculus: The study of differentiation is intrinsically linked to its inverse process, integration. The Fundamental Theorem of Calculus, which you will encounter next, provides the profound connection between the derivative and the integral. A strong grasp of derivatives is essential for understanding and applying techniques of integration.
- Multivariable Calculus: The principles we have developed for functions of a single variable, , are directly extended to functions of multiple variables, such as . Concepts like limits and continuity retain their core meaning, while the derivative evolves into partial derivatives and the gradient, which are used to analyze surfaces and vector fields.
- Differential Equations: This vast and critical field is entirely based on equations involving unknown functions and their derivatives. Your ability to differentiate and understand the properties of derivatives is the prerequisite for solving the differential equations that model countless physical and engineering systems.
- Numerical Methods and Optimization: The techniques for finding maxima and minima using derivatives are the cornerstone of optimization theory. In subsequent chapters, these methods will be expanded upon to solve complex engineering optimization problems, often with the aid of numerical algorithms that are themselves based on calculus principles like the Newton-Raphson method.