Limits at Infinity - Complete Interactive Lesson
Part 1: Limits at Infinity & Horizontal Asymptotes
♾️ Limits at Infinity — End Behavior
Part 1 of 4 — What means
Topics in This Part
| Section |
|---|
| The Idea of |
| 🔑 Horizontal Asymptotes |
| Quick Reference Table |
🔑 Why this matters: End behavior governs horizontal asymptotes — a foundational topic for both limits and integration later.
💡 What Does Mean?
As gets arbitrarily large, gets arbitrarily close to .
We are not plugging into — isn't a number. We're asking: as marches off to the right, where is headed?
Same idea for — march to the left.
💡 The two ends are independent: might approach different limits as and as .
🔑 Horizontal Asymptotes
The line is a horizontal asymptote of if or .
A function can have:
- 0 horizontal asymptotes (e.g., — both ends )
- 1 horizontal asymptote (e.g., — left end , right end , so on the left only)
- 2 horizontal asymptotes (e.g., — on the left, on the right)
⚠️ A function can cross a horizontal asymptote — it just can't stay away from it forever.
📋 Quick Reference
| Function | ||
|---|---|---|
| undefined | ||
End-Behavior Vocab 🎯
Compute Limits at Infinity 🧮
1)
2)
3) (use pi/2)
Part 2: Rational Functions Compare Degrees
📊 Rational Functions at Infinity
Part 2 of 4 — Compare degrees
Topics in This Part
| Section |
|---|
| 🔑 The Three-Case Rule |
| Why It Works (Divide-By-Highest-Power) |
| Examples |
🔑 Why this matters: Almost every AP "limit at infinity" problem on a rational function is solved by the degree-comparison rule.
🔑 The Three-Case Rule
For with degrees , :
| Case | Result |
|---|---|
| (bottom heavier) | Limit |
| (equal degrees) | Limit |
| (top heavier) | Limit (sign depends on leading coefficients and direction) — DNE as a finite limit |
💡 Memorize this. It's the single most useful rule in this section.
🛠️ Why It Works — Divide By Highest Power
Take . Divide top and bottom by :
As , and :
The non-leading terms become negligible, leaving just the ratio of leading coefficients.
📝 Examples
| Limit | Case | Answer |
|---|---|---|
Apply the Three-Case Rule 🎯
Compute 🧮
1)
2)
3)
Part 3: Radicals at Infinity
√ Radicals at Infinity
Part 3 of 4 — Be careful with when
Topics in This Part
| Section |
|---|
| The "Effective Degree" of a Radical |
| 🔑 The Trap |
| Worked Example for |
🔑 Why this matters: A square root contributes "half a degree." And the sign on matters when is negative.
📐 Effective Degree
For end behavior, behaves like in size — it has "effective degree 1." More generally, has effective degree .
Example. .
- Numerator effective degree 1; denominator degree 1 → equal.
- Leading behavior: numerator , denominator . Ratio .
So this limit is as .
⚠️ The Trap
The identity is:
So when , (positive), not . This sign change matters.
Worked example. .
- Divide top and bottom by (since ):
- As : numerator , denominator .
Answer: .
💡 Compare: as the same expression gives . The two ends differ in sign.
🚀 Shortcut: Look at Leading Behavior
For as :
- :
- : (because we need a positive output and is negative)
This shortcut handles most AP problems quickly.
Sign-Aware Limits 🎯
Practice 🧮
1)
2)
Part 4: Exponentials, Logs, and DNE Cases
🌐 Other Cases — Exponentials, Logs, and Oscillation
Part 4 of 4 — Beyond rationals
Topics in This Part
| Section |
|---|
| Exponentials Win the Growth Race |
| Logs Lose the Growth Race |
| When Limits at Infinity DNE |
🔑 Why this matters: Many limit-at-infinity problems involve , , or oscillating functions. Each has its own rules.
🚀 Exponentials Beat Polynomials
For any positive : grows faster than . So
Example. . (Even with a huge polynomial, the exponential wins.)
For : , so things like (still exponential dominates the polynomial).
🐢 Logs Lose to Polynomials
For any positive : grows slower than .
Growth hierarchy (slowest to fastest, going to ):
🚫 When the Limit at Infinity DNE
Some functions don't settle to a value or to at infinity:
- , as — oscillate forever between and . DNE.
- — amplitude grows, oscillates between . DNE.
But:
- as (Squeeze Theorem: bounded numerator, growing denominator).
💡 Bounded over growing gives 0. Growing × bounded oscillation fails to converge.
Beyond Rationals 🎯
Exit Check ✅