3.1 Graphs of Polynomials
Three of the families of functions studied thus far – constant, linear and quadratic – belong to a much larger group of functions called polynomials. We begin our formal study of general polynomials with a definition and some examples.
There are several things about Definition that may be off-putting or downright frightening. The best thing to do is look at an example. Consider . Is this a polynomial function? We can re-write the formula for as Comparing this with Definition, we identify , , , , , and . In other words, is the coefficient of , is the coefficient of , and so forth; the subscript on the 's merely indicates to which power of the coefficient belongs. The business of restricting to be a natural number lets us focus on well-behaved algebraic animals.1
The reader may well wonder why we have chosen to separate off constant functions from the other polynomials in Definition. Why not just lump them all together and, instead of forcing to be a natural number, , allow to be a whole number, . We could unify all of the cases, since, after all, isn't ? The answer is `yes, as long as .' The function and are different, because their domains are different. The number is defined, whereas is not.4 Indeed, much of the theory we will develop in this chapter doesn't include the constant functions, so we might as well treat them as outsiders from the start. One good thing that comes from Definition is that we can now think of linear functions as degree (or `first degree') polynomial functions and quadratic functions as degree (or `second degree') polynomial functions.
Our next example shows how polynomials of higher degree arise `naturally'5 in even the most basic geometric applications.
In order to solve Example Example 3, we made good use of the graph of the polynomial , so we ought to turn our attention to graphs of polynomials in general. Below are the graphs of , and , side-by-side. We have omitted the axes to allow you to see that as the exponent increases, the `bottom' becomes `flatter' and the `sides' become `steeper.' If you take the the time to graph these functions by hand,8 you will see why.
All of these functions are even, (Do you remember how to show this?) and it is exactly because the exponent is even.9 This symmetry is important, but we want to explore a different yet equally important feature of these functions which we can be seen graphically – their end behavior.
The end behavior of a function is a way to describe what is happening to the function values (the -values) as the -values approach the `ends' of the -axis.10 That is, what happens to as becomes small without bound11 (written ) and, on the flip side, as becomes large without bound12 (written ).
For example, given , as , we imagine substituting , , etc., into to get , , and so on. Thus the function values are becoming larger and larger positive numbers (without bound). To describe this behavior, we write: as , . If we study the behavior of as , we see that in this case, too, . (We told you that the symmetry was important!) The same can be said for any function of the form where is an even natural number. If we generalize just a bit to include vertical scalings and reflections across the -axis,13 we have
End Behavior of functions , even.
Suppose where is a real number and is an even natural number. The end behavior of the graph of matches one of the following:
- for , as , and as ,
- for , as , and as ,
Graphically:
We now turn our attention to functions of the form where is an odd natural number. (We ignore the case when , since the graph of is a line and doesn't fit the general pattern of higher-degree odd polynomials.) Below we have graphed , , and . The `flattening' and `steepening' that we saw with the even powers presents itself here as well, and, it should come as no surprise that all of these functions are odd.14 The end behavior of these functions is all the same, with as and as .
As with the even degreed functions we studied earlier, we can generalize their end behavior.
End Behavior of functions , odd.
Suppose where is a real number and is an odd natural number. The end behavior of the graph of matches one of the following:
- for , as , and as ,
- for , as , and as ,
Graphically:
Despite having different end behavior, all functions of the form for natural numbers share two properties which help distinguish them from other animals in the algebra zoo: they are continuous and smooth. While these concepts are formally defined using Calculus,15 informally, graphs of continuous functions have no `breaks' or `holes' in them, and the graphs of smooth functions have no `sharp turns'. It turns out that these traits are preserved when functions are added together, so general polynomial functions inherit these qualities. Below we find the graph of a function which is neither smooth nor continuous, and to its right we have a graph of a polynomial, for comparison. The function whose graph appears on the left fails to be continuous where it has a `break' or `hole' in the graph; everywhere else, the function is continuous. The function is continuous at the `corner' and the `cusp', but we consider these `sharp turns', so these are places where the function fails to be smooth. Apart from these four places, the function is smooth and continuous. Polynomial functions are smooth and continuous everywhere, as exhibited in the graph on the right.
The notion of smoothness is what tells us graphically that, for example, , whose graph is the characteristic `' shape, cannot be a polynomial. The notion of continuity is what allowed us to construct the sign diagram for quadratic inequalities as we did in Section. This last result is formalized in the following theorem.
The Intermediate Value Theorem is extremely profound; it gets to the heart of what it means to be a real number, and is one of the most often used and under appreciated theorems in Mathematics. With that being said, most students see the result as common sense since it says, geometrically, that the graph of a polynomial function cannot be above the -axis at one point and below the -axis at another point without crossing the -axis somewhere in between. The following example uses the Intermediate Value Theorem to establish a fact that that most students take for granted. Many students, and sadly some instructors, will find it silly.
Our primary use of the Intermediate Value Theorem is in the construction of sign diagrams, as in Section, since it guarantees us that polynomial functions are always positive or always negative on intervals which do not contain any of its zeros. The general algorithm for polynomials is given below.
Steps for Constructing a Sign Diagram for a Polynomial Function
Suppose is a polynomial function.
- Find the zeros of and place them on the number line with the number above them.
- Choose a real number, called a test value, in each of the intervals determined in step 1.
- Determine the sign of for each test value in step 2, and write that sign above the corresponding interval.
A couple of notes about the Example Example 5 are in order. First, note that we purposefully did not label the -axis in the sketch of the graph of . This is because the sign diagram gives us the zeros and the relative position of the graph - it doesn't give us any information as to how high or low the graph strays from the -axis. Furthermore, as we have mentioned earlier in the text, without Calculus, the values of the relative maximum and minimum can only be found approximately using a calculator. If we took the time to find the leading term of , we would find it to be . Looking at the end behavior of , we notice that it matches the end behavior of . This is no accident, as we find out in the next theorem.
To see why Theorem is true, let's first look at a specific example. Consider . If we wish to examine end behavior, we look to see the behavior of as . Since we're concerned with 's far down the -axis, we are far away from so can rewrite for these values of as
As becomes unbounded (in either direction), the terms and become closer and closer to , as the table below indicates.
In other words, as , , which is the leading term of . The formal proof of Theorem works in much the same way. Factoring out the leading term leaves
As , any term with an in the denominator becomes closer and closer to , and we have . Geometrically, Theorem says that if we graph using a graphing calculator, and continue to `zoom out', the graph of it and its leading term become indistinguishable. Below are the graphs of (the thicker line) and (the thinner line) in two different windows.


A view `close' to the origin.
A `zoomed out' view.
Let's return to the function in Example Example 5, , whose sign diagram and graph are reproduced below for reference. Theorem tells us that the end behavior is the same as that of its leading term . This tells us that the graph of starts and ends above the -axis. In other words, is as , and as a result, we no longer need to evaluate at the test values and . Is there a way to eliminate the need to evaluate at the other test values? What we would really need to know is how the function behaves near its zeros - does it cross through the -axis at these points, as it does at and , or does it simply touch and rebound like it does at . From the sign diagram, the graph of will cross the -axis whenever the signs on either side of the zero switch (like they do at and ); it will touch when the signs are the same on either side of the zero (as is the case with ). What we need to determine is the reason behind whether or not the sign change occurs.
Fortunately, was given to us in factored form: . When we attempt to determine the sign of , we are attempting to find the sign of the number , which works out to be which is . If we move to the other side of , and find the sign of , we are determining the sign of , which is which gives us the . Notice that signs of the first two factors in both expressions are the same in and . The only factor which switches sign is the third factor, , precisely the factor which gave us the zero . If we move to the other side of and look closely at , we get the sign pattern or and we note that, once again, going from to , the only factor which changed sign was the first factor, , which corresponds to the zero . Finally, to find , we substitute to get which is or . The sign didn't change for the middle factor . Even though this is the factor which corresponds to the zero , the fact that the quantity is squared kept the sign of the middle factor the same on either side of . If we look back at the exponents on the factors and , we see that they are both odd, so as we substitute values to the left and right of the corresponding zeros, the signs of the corresponding factors change which results in the sign of the function value changing. This is the key to the behavior of the function near the zeros. We need a definition and then a theorem.
Hence, rewriting as , we see that is a zero of multiplicity , is a zero of multiplicity and is a zero of multiplicity .
Our last example shows how end behavior and multiplicity allow us to sketch a decent graph without appealing to a sign diagram.
Exercises
In Exercises -, find the degree, the leading term, the leading coefficient, the constant term and the end behavior of the given polynomial.
- ,
- ,
- ,
- ,
- ,
- ,
- Use the Intermediate Value Theorem to prove that has a real zero in each of the following intervals: and .
- Rework Example Example 3 assuming the box is to be made from an 8.5 inch by 11 inch sheet of paper. Using scissors and tape, construct the box. Are you surprised?17
- Use a graphing utility to graph and determine the number of TVs which should be sold to maximize revenue. What is the maximum revenue?
- Assume that the cost, in thousands of dollars, to produce hundred LCD TVs is given by for . Find and simplify an expression for the profit function . (Remember: Profit = Revenue - Cost.)
- Use a graphing utility to graph and determine the number of TVs which should be sold to maximize profit. What is the maximum profit?
- While developing their newest game, Sasquatch Attack!, the makers of the PortaBoy (from Example ) revised their cost function and now use , for . As before, is the cost to make PortaBoy Game Systems. Market research indicates that the demand function remains unchanged. Use a graphing utility to find the production level that maximizes the profit made by producing and selling PortaBoy game systems.
According to US Postal regulations, a rectangular shipping box must satisfy the inequality “Length + Girth 130 inches” for Parcel Post and “Length + Girth 108 inches” for other services. Let's assume we have a closed rectangular box with a square face of side length as drawn below. The length is the longest side and is clearly labeled. The girth is the distance around the box in the other two dimensions so in our case it is the sum of the four sides of the square, .
- Assuming that we'll be mailing a box via Parcel Post where Length + Girth 130 inches, express the length of the box in terms of and then express the volume of the box in terms of .
- Find the dimensions of the box of maximum volume that can be shipped via Parcel Post.
- Repeat parts and if the box is shipped using “other services”.
Figure 3.24 We now revisit the data set from Exercise in Section. In that exercise, you were given a chart of the number of hours of daylight they get on the of each month in Fairbanks, Alaska based on the 2009 sunrise and sunset data found on the U.S. Naval Observatory website. We let represent January 21, 2009, represent February 21, 2009, and so on. The chart is given again for reference.
Table 3.1 Month Number 1 2 3 4 5 6 7 8 9 10 11 12 Hours of Daylight 5.8 9.3 12.4 15.9 19.4 21.8 19.4 15.6 12.4 9.1 5.6 3.3 Find cubic (third degree) and quartic (fourth degree) polynomials which model this data and comment on the goodness of fit for each. What can we say about using either model to make predictions about the year 2020? (Hint: Think about the end behavior of polynomials.) Use the models to see how many hours of daylight they got on your birthday and then check the website to see how accurate the models are. Knowing that Sasquatch are largely nocturnal, what days of the year according to your models are going to allow for at least 14 hours of darkness for field research on the elusive creatures?
An electric circuit is built with a variable resistor installed. For each of the following resistance values (measured in kilo-ohms, ), the corresponding power to the load (measured in milliwatts, ) is given in the table below. 18
Table 3.2 Resistance: () 1.012 2.199 3.275 4.676 6.805 9.975 Power: () 1.063 1.496 1.610 1.613 1.505 1.314 - Make a scatter diagram of the data using the Resistance as the independent variable and Power as the dependent variable.
- Use your calculator to find quadratic (2nd degree), cubic (3rd degree) and quartic (4th degree) regression models for the data and judge the reasonableness of each.
- For each of the models found above, find the predicted maximum power that can be delivered to the load. What is the corresponding resistance value?
- Discuss with your classmates the limitations of these models - in particular, discuss the end behavior of each.
- Show that the end behavior of a linear function is as it should be according to the results we've established in the section for polynomials of odd degree.19 (That is, show that the graph of a linear function is “up on one side and down on the other” just like the graph of for odd numbers .)
- There is one subtlety about the role of multiplicity that we need to discuss further; specifically we need to see `how' the graph crosses the -axis at a zero of odd multiplicity. In the section, we deliberately excluded the function from the discussion of the end behavior of for odd numbers and we said at the time that it was due to the fact that didn't fit the pattern we were trying to establish. You just showed in the previous exercise that the end behavior of a linear function behaves like every other polynomial of odd degree, so what doesn't do that does? It's the `flattening' for values of near zero. It is this local behavior that will distinguish between a zero of multiplicity 1 and one of higher odd multiplicity. Look again closely at the graphs of and from Exercise. Discuss with your classmates how the graphs are fundamentally different at the origin. It might help to use a graphing calculator to zoom in on the origin to see the different crossing behavior. Also compare the behavior of to that of near the point . What do you predict will happen at the zeros of ?
Here are a few other questions for you to discuss with your classmates.
- How many local extrema could a polynomial of degree have? How few local extrema can it have?
- Could a polynomial have two local maxima but no local minima?
- If a polynomial has two local maxima and two local minima, can it be of odd degree? Can it be of even degree?
- Can a polynomial have local extrema without having any real zeros?
- Why must every polynomial of odd degree have at least one real zero?
- Can a polynomial have two distinct real zeros and no local extrema?
- Can an -intercept yield a local extrema? Can it yield an absolute extrema?
- If the -intercept yields an absolute minimum, what can we say about the degree of the polynomial and the sign of the leading coefficient?
In Exercises -, find the real zeros of the given polynomial and their corresponding multiplicities. Use this information along with a sign chart to provide a rough sketch of the graph of the polynomial. Compare your answer with the result from a graphing utility.
In Exercises -, given the pair of functions and , sketch the graph of by starting with the graph of and using transformations. Track at least three points of your choice through the transformations. State the domain and range of .
In Exercises -, suppose the revenue , in thousands of dollars, from producing and selling hundred LCD TVs is given by for .
Answers
- Degree 2 Leading term Leading coefficient Constant term As As
- Degree 5 Leading term Leading coefficient Constant term As As
- Degree 4 Leading term Leading coefficient Constant term As As
- Degree 3 Leading term Leading coefficient Constant term As As
- Degree 17 Leading term Leading coefficient Constant term As As
- Degree 2 Leading term Leading coefficient Constant term As As
- Degree 4 Leading term Leading coefficient Constant term As As
- Degree 5 Leading term Leading coefficient Constant term As As
- Degree 6 Leading term Leading coefficient Constant term As As
- Degree 3 Leading term Leading coefficient Constant term As As
multiplicity 1 multiplicity 2
Figure 3.25 multiplicity 1 multiplicity 3
Figure 3.26 multiplicity 2 multiplicity 1
Figure 3.27 multiplicity 2 multiplicity 1
Figure 3.28 multiplicity 3 multiplicity 2
Figure 3.29 multiplicity 1 multiplicity 1 multiplicity 1 multiplicity 1
Figure 3.30 multiplicity 2 multiplicity 4
Figure 3.31 multiplicity 2 multiplicity 2 multiplicity 2
Figure 3.32 multiplicity 1
Figure 3.33 multiplicity 1 multiplicity 1 multiplicity 1
Figure 3.34 domain: range:
Figure 3.35 domain: range:
Figure 3.36 domain: range:
Figure 3.37 domain: range:
Figure 3.38 domain: range:
Figure 3.39 domain: range:
Figure 3.40 - We have and so the Intermediate Value Theorem tells us that has real zeros in the intervals and .
- , . Volume is maximized when , so the dimensions of the box with maximum volume are: height 1.58 inches, width 5.34 inches, and depth 7.84 inches. The maximum volume is 66.15 cubic inches.
- The calculator gives the location of the absolute maximum (rounded to three decimal places) as and . Since represents the number of TVs sold in hundreds, corresponds to TVs. Since we can't sell half of a TV, we compare and , so selling TVs results in a (slightly) higher revenue. Since represents the revenue in thousands of dollars, the maximum revenue is .
- , .
- The calculator gives the location of the absolute maximum (rounded to three decimal places) as and . Since represents the number of TVs sold in hundreds, corresponds to TVs. Since we can't sell of a TV, we compare and , so selling TVs results in a (slightly) higher revenue. Since represents the revenue in thousands of dollars, the maximum revenue is .
- Making and selling 71 PortaBoys yields a maximized profit of $5910.67.
- Our ultimate goal is to maximize the volume, so we'll start with the maximum Length Girth of This means the length is . The volume of a rectangular box is always length width height so we get .
- Graphing on shows a maximum at so the dimensions of the box with maximum volume are for a volume of .
- If we start with Length Girth then the length is and the volume is . Graphing on shows a maximum at so the dimensions of the box with maximum volume are for a volume of . (Calculus will confirm that the measurements which maximize the volume are exactly 18in. by 18in. by 36in., however, as I'm sure you are aware by now, we treat all calculator results as approximations and list them as such.)
The cubic regression model is . It has which isn't bad. The graph of in the viewing window along with the scatter plot is shown below on the left. Notice that hits the -axis at about making this a bad model for future predictions. To use the model to approximate the number of hours of sunlight on your birthday, you'll have to figure out what decimal value of is close enough to your birthday and then plug it into the model. My (Jeff's) birthday is July 31 which is 10 days after July 21 (). Assuming 30 days in a month, I think should work for my birthday and . The website says there will be about hours of daylight that day. To have 14 hours of darkness we need 10 hours of daylight. We see that and so it seems reasonable to say that we'll have at least 14 hours of darkness from December 21, 2008 () to February 21, 2009 () and then again from October 21,2009 () to December 21, 2009 ().
The quartic regression model is . It has which is good. The graph of in the viewing window along with the scatter plot is shown below on the right. Notice that is above making this a bad model as well for future predictions. However, making it much better at predicting the hours of daylight on July 31 (my birthday). This model says we'll have at least 14 hours of darkness from December 21, 2008 () to about March 1, 2009 () and then again from October 10, 2009 () to December 21, 2009 ().

Figure 3.41 
Figure 3.42 - The scatter plot is shown below with each of the three regression models.
- The quadratic model is with . The cubic model is with . The quartic model is with .
- The maximums predicted by the three models are , and , respectively.

Figure 3.43 
Figure 3.44 
Figure 3.45
Adapted from Precalculus, 3rd corrected edition, by Carl Stitz and Jeff Zeager (stitz-zeager.com), licensed under CC BY-NC-SA 3.0. Changes were made: reformatted as an accessible XYZ web edition. License: CC-BY-NC-SA-3.0.