Derivatives — Rules, Chain Rule, Implicit Differentiation
The derivative measures instantaneous rate of change. A small set of rules (power, sum, product, quotient) plus the chain rule (for compositions) and implicit differentiation (for relations not solved for ) let you differentiate virtually any function built from elementary pieces. Used everywhere rates matter — physics, economics, engineering. Codified by Newton and Leibniz (1660s–1680s).
Differentiation is local and linear. Near any point, a smooth function looks like a straight line, and the derivative is that line's slope. Because the operation is linear and respects how functions are built (added, multiplied, composed), each construction rule has a matching derivative rule. The chain rule is the deepest: rates of change multiply along a chain of dependencies.
Formal Statement
The derivative of at is
Derivation hint: this is the limit of the slope of a secant line through and as the second point slides toward the first. Here is a small increment in the input; is the resulting change in output; their ratio is the average rate of change, and the limit is the instantaneous rate of change. Notations: , , , .
Let and be differentiable functions of , and , constants.
Constant rule:
Derivation hint: a constant function has , so the difference quotient is for all .
Power rule:
Derivation hint: expand with the binomial theorem; the linear-in- term gives , higher powers vanish in the limit.
Constant multiple rule:
Derivation hint: factor the constant out of the difference quotient and out of the limit.
Sum rule:
Derivation hint: split the difference quotient of into the difference quotients of and ; the limit of a sum is the sum of limits.
Product rule:
Derivation hint: add and subtract in the numerator to split into two difference quotients.
Quotient rule:
Derivation hint: write as and combine the product rule with the chain rule applied to .
If — a composition — then
Derivation hint: write the difference quotient as and let both increments shrink; the outer rate times the inner rate. In Leibniz notation, with :
Derivation hint: the differentials "cancel" formally — a mnemonic justified rigorously by the limit argument above.
If a relation defines as a function of (at least locally), differentiate both sides with respect to , treating as a function of and applying the chain rule to every -term. Then solve algebraically for . For example, from :
Derivation hint: by the chain rule, since depends on ; isolate .
Why It Holds
We compute the limit directly.
Step 1. Start from the definition applied to :
Derivation hint: just substitute into equation [1].
Step 2. Add and subtract in the numerator:
Derivation hint: this clever insertion creates two recognizable difference quotients without changing the value.
Step 3. Split the limit and recognize each piece:
Derivation hint: limit of a sum splits; constants relative to pull out.
Step 4. As : (continuity, since is differentiable), the first quotient , the second . Hence
Derivation hint: substitute each limit; this is equation [6] rearranged.
∎Newton developed his "method of fluxions" in the mid-1660s while sheltering from the plague at Woolsthorpe. He thought of variables as flowing quantities (, ) whose rates of change he called fluxions (written , ). His motivation was physical: velocity is the fluxion of position, acceleration the fluxion of velocity. Newton's notation survives today in physics, where means . He used these ideas to derive Kepler's laws from his law of gravitation in the Principia (1687).
Building Intuition
Think of the chain rule as gears. If gear A turns 3 times for each turn of gear B, and gear B turns 2 times for each turn of gear C, then A turns times per turn of C. Rates multiply through the linkage. That product is exactly equation [9]. For implicit differentiation, picture standing on a circle. You cannot write "the" as one function of (the top and bottom semicircles disagree), but at any single point the curve still has a definite tangent slope. Implicit differentiation finds that slope without forcing you to pick a branch — it works with the relation as a whole.
Worked Examples
Given: . Find .
Step 1. Identify the composition. Outer function: . Inner function: .
Step 2. Differentiate outer: .
Step 3. Differentiate inner: .
Step 4. Multiply (equation [9]):
Derivation hint: outer derivative evaluated at the inner function, times the inner derivative.
Check at : .
Given: the ellipse . Find the slope of the tangent at the point .
Step 1. Differentiate both sides with respect to , treating as :
Derivation hint: by the chain rule.
Step 2. Solve for :
Derivation hint: subtract , divide by .
Step 3. Substitute the point :
Verify the point is on the curve: ✓
Common Misconceptions
The product rule is NOT . Many students guess . This is wrong — you must use equation [6], . Test it: , but .
Don't forget the inner derivative. Writing is incomplete — you must multiply by , giving . The missing factor is the single most common chain-rule error.
In implicit differentiation, is a function, not a constant. is not ; it is .
Consider and . If the false rule held, then . But the correct power rule gives . Since in general (they're equal only at and ), the naive product "rule" fails — confirming the genuine product rule [6] is needed.
Connections
These rules are the computational engine of calculus. They depend on Limits and Continuity, since every rule is ultimately a limit of difference quotients. They feed directly into Applications of Derivatives — finding maxima, minima, and rates. The chain rule reappears as the heart of Related Rates, where quantities change in time, and of Integration by Substitution, which reverses it. Implicit differentiation generalizes into Partial Derivatives and the multivariable chain rule. Together they make The Fundamental Theorem of Calculus computationally usable.
Real-World Applications
Historical Development
Subtleties & Limits
The rules above assume differentiability, which is stronger than continuity. The function is continuous everywhere but has no derivative at (the left and right slopes disagree). More dramatically, the Weierstrass function is continuous everywhere yet differentiable nowhere — a function so jagged it has no tangent at any point. Implicit differentiation also has a hidden assumption: that actually defines as a function near the point of interest. The Implicit Function Theorem specifies exactly when this works — roughly, when . At points where it vanishes (like the top/bottom of a circle, where the tangent is vertical), is undefined or infinite, and the method must be handled with care.
See Also
Limits and Continuity · Applications of Derivatives · Related Rates · The Fundamental Theorem of Calculus · Trigonometric Functions · Integration by Substitution