Chapter 2: Problem 61
Determine whether each statement is true or false. A polynomial function of degree \(n, n>0\) must have at least one zero.
Short Answer
Expert verified
The statement is true.
Step by step solution
01
Understanding Polynomial Functions
A polynomial function of degree \(n\) is written in the form \(f(x) = a_n x^n + a_{n-1} x^{n-1} + \ldots + a_1 x + a_0\), where \(a_n eq 0\). The degree \(n\) of the polynomial is the highest power of \(x\) that appears with a nonzero coefficient.
02
Defining a Zero of a Function
A zero of a function \(f(x)\) is a value \(x = c\) such that \(f(c) = 0\). For polynomials, zeros are the solutions to the equation \(f(x) = 0\).
03
Applying the Fundamental Theorem of Algebra
The Fundamental Theorem of Algebra states that every non-constant polynomial function has at least one complex zero. Thus, if \(n > 0\), the polynomial must have at least one zero.
04
Analyzing the Given Statement
The statement in the problem says a polynomial function of degree \(n, n>0\) must have at least one zero. According to the Fundamental Theorem of Algebra, this statement is true, as the theorem guarantees at least one complex zero.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Degree of a Polynomial
In the realm of polynomial functions, one of the fundamental concepts is the **degree** of a polynomial. Let's break this down.
The degree of a polynomial is essentially the highest power of the variable, typically denoted as "\(x\)," that has a non-zero coefficient. In more formal terms, for a polynomial expressed as \[f(x) = a_n x^n + a_{n-1} x^{n-1} + \ldots + a_1 x + a_0,\]like the above equation, the degree is represented by "\(n\)." Here, "\(a_n\)" must not be zero for "\(n\)" to be the degree.
Understanding the degree of a polynomial gives insight into various properties of the function, such as:
The degree of a polynomial is essentially the highest power of the variable, typically denoted as "\(x\)," that has a non-zero coefficient. In more formal terms, for a polynomial expressed as \[f(x) = a_n x^n + a_{n-1} x^{n-1} + \ldots + a_1 x + a_0,\]like the above equation, the degree is represented by "\(n\)." Here, "\(a_n\)" must not be zero for "\(n\)" to be the degree.
Understanding the degree of a polynomial gives insight into various properties of the function, such as:
- The number of possible real or complex zeros.
- The behavior of the graph as it approaches infinity.
- The total number of solutions when the polynomial is set to zero.
Zero of a Function
The concept of a **zero** of a function is pivotal in solving polynomial equations. A zero of a function \(f(x)\) is a special value, denoted as \(x = c\), where the function equals zero. In other words:\[f(c) = 0\]Zeros are also known as roots or solutions, especially in the context of polynomial equations when solving \(f(x) = 0\).
Why are zeros important? They're vital since:
Why are zeros important? They're vital since:
- They indicate points where the graph intersects the x-axis.
- They help in factoring polynomials into linear components when possible.
- They provide insights into the structure and characteristics of the polynomial.
Fundamental Theorem of Algebra
The **Fundamental Theorem of Algebra** is a key principle that asserts a profound truth about polynomial equations. It states that any non-constant polynomial of degree "\(n\)", where \(n > 0\), possesses at least one complex zero.
This theorem is critical because:
This theorem solidifies our confidence in exploring and solving polynomial equations irrespective of their complexity.
This theorem is critical because:
- It guarantees that every polynomial has a solution in the complex number system.
- It implies that a polynomial of degree "\(n\)" will have precisely "\(n\)" solutions, if counting both real and complex zeros, considering their multiplicities.
- It forms a foundational principle in algebra, linking polynomials to complex analysis.
This theorem solidifies our confidence in exploring and solving polynomial equations irrespective of their complexity.