Welcome! Today we're exploring Understanding Zeros of a Polynomial — one of the most important ideas in the entire polynomials chapter.
When you evaluated at and got 0key result, that was not a coincidence — it tells you something fundamental about the polynomial.
Certain special inputs 'zero out' a polynomial, and these inputs are the key to:
In this lesson, you will learn:
| Concept | What you'll be able to do |
|---|---|
| What a zero is | Define it precisely |
| How to verify a zero | Check if a given value is a zero |
| A powerful rule | Know how many zeros a polynomial can have |
We are about to define the most important concept in the chapter.
A zero is not the polynomial being zero everywhere — it is a specific input value that produces output zero.
Getting this definition precise is essential because every technique in the chapter revolves around it.
Remember when we evaluated at , and the result was 0?
This makes special value special — it 'zeroes out' the polynomial.
Question 🤔
What does it mean for a number to be a 'zero' of a polynomial ?
Is 3check this a zero of ?
Show your verification.
A zero of a polynomial is a specific input value — a number you plug in for — that produces output zero.
Formally: a real number is called a zero of the polynomial if key condition.
In simpler words: if you substitute into the polynomial and get , then is a zero of that polynomial.
Important distinction: the zero is not the polynomial itself being zero. The polynomial is 'alive' at most values of . It just happens to equal zero at certain special inputs.
The word 'zero' refers to the input that makes the output zero — it 'zeroes out' the polynomial.
To verify: substitute and compute.
Since the result is zero!, IS a zero of .
Let's check another value:
Since the result is not not zero, is NOT a zero of .
Now that we know the definition of a zero, we need to be able to verify whether a given value is or is not a zero.
This requires careful substitution — exactly the evaluation skill from the previous section — with the specific goal of checking whether the result equals target.
To check if a value is a zero, substitute it and see if the result is exactly 0.
For :
| Input | Calculation | Result | Conclusion |
|---|---|---|---|
| zero! | 3 is a zero | ||
| not zero | 0 is not a zero |
Your turn! ✏️
Is a zero of ?
Is a zero of ?
Show complete working for both.
Let's verify carefully.
For x = -1:
(even power, positive).
(negative times negative = positive).
So . The result is 0key!, so -1 IS a zero.
For x = 2:
The result is , which is not . So 2 is NOT a zero of .
The Verification Sequence
Every time you check whether a value is a zero, follow these four steps:
This four-step process is what you do every single time — whether checking , , or any other value.
We've seen how to verify individual zeros — plug in a value, check if the output is .
But here's an interesting question:
How many zeros can a polynomial have?
There's actually a rule that connects the degree of a polynomial to the maximum number of real zeros it can have.
This rule is incredibly useful — it acts as a built-in error detector for your work.
Consider the polynomial .
This is a degree 2 polynomial (a quadratic).
We found that it has two zeros:
Think about this: 🤔
A polynomial of degree has at most how many real zeros?
And here's a scenario:
If a student claims to have found 3 zeros for a quadratic polynomial, what should they conclude?
Here is the rule: A polynomial of degree has at most real zeros.
This is a fundamental constraint — no exceptions!
| Polynomial Type | Degree | Maximum Real Zeros |
|---|---|---|
| Linear | 1 | 1 |
| Quadratic | 2 | 2 |
| Cubic | 3 | 3 |
| Biquadratic | 4 | 4 |
The degree tells you the ceiling — the maximum possible real zeros.
So if a student claims to have found 3 zeros for a quadratic polynomial — that's impossible! They must have made a calculation error somewhere.
Why 'at most' and not 'exactly'? Because some polynomials have fewer real zeros than their degree allows.
This is a crucial distinction — the degree gives you the ceiling, not a guarantee.
Example 1: has degree 2 but zero real zeros.
Why? Because for all real , so . The polynomial is always at least 1 — it never touches the x-axis.
Example 2: has degree 2 but only one distinct real zero — namely .
We say this zero has multiplicity 2 because the factor appears twice.
The Degree Rule as an Error Detector
The rule is your error detector: if you find more zeros than the degree allows, you have made a mistake.
Using the Check
This check catches errors before they go unnoticed.
For example, if you're working with the quadratic polynomial (degree 2) and you claim to have found 3 zeros, something has gone wrong in your calculation!
We verified that this polynomial has exactly 2 zeros: and . That's the maximum allowed for a quadratic.
The at-most-n rule sets a ceiling, not a floor.
Understanding when a polynomial has fewer zeros than its degree allows — and why — deepens your understanding and prepares you for cases like:
Consider these two quadratics:
Both are quadratics, but they have different numbers of distinct real zeros.
Take a look at the graphs on the board — on the left and on the right.
Question 🤔
How many distinct real zeros does have?
How many does have?
Explain why each has fewer than 2 distinct zeros.
The degree sets the ceiling for the number of real zeros, but a polynomial can have fewer.
This is exactly why we say "at most" — the degree tells you the maximum possible, not a guarantee.
Let's see two important cases where this happens — and both are sitting right in front of us with and .
Case 1: No real zeros at all.
has degree 2, but for any real , we know . So — it never touches 0. This means zero real zeroskey!.
Look at the parabola on the canvas — it floats entirely above the x-axis, never crossing it. The vertex sits at the point , which is the lowest the curve ever goes.
Case 2: Repeated zeros.
has degree 2. It equals 0 only when , giving . That's one distinct zero.
But the factor appears twice, so we say has multiplicity 2'.
Counting with multiplicity, there are 2 zeros (both equal to 3), which is consistent with degree 2.
So a degree-2 polynomial can have 0, 1, or 2 distinct real zeros. The degree is the maximum, not the guaranteed count.
Look at the three parabolas on the board — they tell the whole story:
This understanding prevents you from worrying when a problem yields fewer zeros than expected — it's completely normal!
In exams: If you find fewer zeros than the degree, don't panic and don't invent extra zeros. Check your work, but trust the math — some polynomials genuinely have fewer real zeros.