2.2 Constant multiple rule
In this section and the next, you’ll see two ways in which you can use formulas that you know for the derivatives of functions to find formulas for the derivatives of other, related functions.
First, suppose that you know the formula for the derivative of a particular function, and you want to know the formula for the derivative of a constant multiple of the function. For example, you already know the formula for the derivative of the function , but suppose that you want to know the formula for the derivative of the function . Let’s think about how the formula for the derivative of the second function can be worked out from the formula for the derivative of the first function.
When you multiply a function by a constant, the effect on its graph is that, for each -value, the corresponding -value is multiplied by the constant. So the graph is stretched or squashed vertically, and, if the constant is negative, then it’s also reflected in the -axis. These effects are called vertical scalings. For example, Figure 24 shows the graphs of , , and , and the point with -coordinate 1 on each of these graphs.
You can see the following effects.
-
Multiplying the function by the constant 3 scales its graph vertically by a factor of 3 (which stretches it).
-
Multiplying the function by the constant scales its graph vertically by a factor of (which squashes it).
-
Multiplying the function by the constant scales its graph vertically by a factor of (which reflects it in the -axis).
The stretching or squashing, and possible reflection, of the graph causes the gradient at each -value to change. For example, you can see that, at the point with -coordinate 1, the graph of is steeper than the graph of .
To see exactly how the gradients change, first consider what happens to the gradient of a straight line when you scale it vertically by a particular factor, say . The scaled line will go up by times as many units for every one unit that it goes along, compared to the unscaled line. In other words, its gradient is multiplied by the factor . For example, Figure 25(a) illustrates what happens when you take a straight line with gradient 1 and scale it vertically by a factor of 3.
The same thing happens for any graph: if you scale it vertically by a particular factor, then its gradient at any particular -value is multiplied by this factor. For example, Figure 25(b) illustrates that if you take a curve that has gradient 1 at a particular -value, and scale it vertically by a factor of 3, then the new curve has gradient 3 at that -value.

So, if you multiply a function by a constant, then its derivative is multiplied by the same constant. This fact can be stated as in the box below.
Constant multiple rule (Lagrange notation)
If the function is given by , where is a function and is a constant, then
for all values of at which is differentiable.
For example, since the derivative of is , it follows by the constant multiple rule that
-
the derivative of is
-
the derivative of is
-
the derivative of is .
The third of these follows because taking a negative is the same as multiplying by . It’s useful to remember in general that if and are functions such that , then, by the constant multiple rule,
for all values of at which is differentiable. Like everything involving derivatives, the constant multiple rule can also be stated in Leibniz notation, as follows.
Constant multiple rule (Leibniz notation)
If , where is a function of and is a constant, then
for all values of at which is differentiable.
(The phrase ‘ is differentiable’ in the box above is a condensed way of saying that if we write then is differentiable at .)
The constant multiple rule can be proved formally by using the idea of differentiation from first principles, and you’ll see this done at the end of this section. First, however, you should concentrate on learning to use it. Here’s an example.
Example 3 Using the constant multiple rule
Differentiate the following functions.
a.
b.
c.
Solution
a.
The derivative is 8 times the derivative of .
b.
The derivative is the negative of the derivative of .
, so
c.
The derivative is 3 times the derivative of .
, so
Here are some examples for you to try. Notice that in some of them the letters used are not the standard ones, , and .
Activity 8 Using the constant multiple rule
Differentiate the following functions.
a.
b.
c.
d.
e.
f.
g.
h.
i.
j.
k.
l.
m.
n.
Answer
a., so
b., so
c., so
d., so
e., so
f., so
g., so
h., so
i., so
j., so
k., so
l., so
m., so
n., so
Activity 9 Using the constant multiple rule to find a gradient
Find the gradient of the graph of the function at the point with -coordinate 2.
Answer
The derivative of the function is
So the gradient of this function at the point with -coordinate 2 is
You saw in the previous section that the function
has derivative
This fact, together with the constant multiple rule, tells you that if is any constant, then the function
has derivative
For example, the function has derivative .
This is as you would expect, because the graph of the function (which is illustrated in Figure 26, in the case where is positive) is a straight line with gradient 0, which means that the gradient at every point on the graph is 0.
This fact about the derivative of a constant function can be stated as follows.
Derivative of a constant function
If is a constant, then
To finish this section, here’s a formal proof of the constant multiple rule, using differentiation from first principles. It uses the Lagrange notation form of the constant multiple rule, which is repeated below.
Constant multiple rule (Lagrange notation)
If the function is given by , where is a function and is a constant, then
for all values of at which is differentiable.
A proof of the constant multiple rule
Suppose that is a function and is a constant. Consider the function given by . Let be any value at which is differentiable. To find , you have to consider what happens to the difference quotient for at , which is
(where can be positive or negative but not zero), as gets closer and closer to zero. Since , the difference quotient for at is equal to
which is equal to
The expression in the large brackets is the difference quotient for at , so, as gets closer and closer to zero, it gets closer and closer to . Hence the whole expression gets closer and closer to . In other words,
which is the constant multiple rule.