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Day 17: Limits, derivatives, and nondifferentiability

Functions and change become calculable through definitions, worked derivations, retrieval, and honest numerical evidence.

Mathematics & Calculus 480 active minutes (8 hours focused study)
01 120 min

Derivative from the limit definition

Agent-Assisted Engineering Check

Prerequisites

Complete the previous activity and use the listed recovery source if blocked.

Learning Objective

Derive f'(a)=lim(h->0)[f(a+h)-f(a)]/h for f(x)=x^2 at a=3, naming h != 0 during cancellation and the two-sided limit assumption.

Instructions

Study source: within this activity's existing reading/practice time, use MIT OCW 18.01SC Single Variable Calculus, Unit 1: Differentiation, Part A: Definition and Basic Rules; worked examples and problem sets, then explain one connection to the local task in your own words. Keep the local exercise and acceptance checks; use its original explanation if the external source is unavailable. 1. Write the definition with the point fixed: f'(3) = lim(h->0) [f(3+h) - f(3)]/h. Say what h is: a nonzero step, positive or negative.
2. Predict the value from Day 16 Activity 4 (secant slopes 6.1, 6.01, ...).
3. Expand f(3+h) completely before subtracting, and subtract f(3) as a whole.
4. Factor h out of the numerator and cancel it, writing "for h != 0" next to the cancellation.
5. Only then let h approach 0 in the simplified expression. The limit is about nearby h, not about h = 0 in the original quotient.
6. Check the result numerically with h = 0.01 and h = -0.01, then repeat the derivation on the practice items.

Time plan (120 min): reading 30 + exercise 60 + check 30. Reading: OpenStax Section 3.1 (defining the derivative). Exercise: items (a)-(c). Check: the mastery item at a=2, unaided, then a numerical check of each result.

Practice & Prediction Log

(a) Write f(3+h), subtract f(3), divide by h, simplify, and take the limit. Do not jump directly to the power rule. (b) Use the same definition for f(x)=x^2 at a general point a. (c) Use the definition for g(x)=1/x at a=2. Check (a) and (c) numerically with h=0.01.

Independent Mastery Criterion

Unaided, derive the same result for f(x)=x^2 at a=2 and state why the derivative is 4.

Authoritative Source Resources & Provenance

linking CC BY-NC-SA 4.0 noncommercial share-alike

MIT OCW 18.01SC Single Variable Calculus

Author: MIT OpenCourseWare (David Jerison) | Original Source Link ↗

Relevant Section / Range: Unit 1: Differentiation, Part A: Definition and Basic Rules; worked examples and problem sets

Verified Version & Date: Public edition checked 2026-11-01; moving pages may change

Selection Rationale:

Independent-study teaching sequence with lectures, worked recitations, problem sets and solutions for Days 16-19; OpenStax remains the numbered written reference.

Source Prerequisites:

Functions, algebra and high-school trigonometry.

Safe Fallback (Offline Resilience):

Use the original localized explanations, exercises and checks already present in this activity; no external account or purchase is required for that fallback.

Compared Candidate Sources & Selection Analysis (2)
OpenStax Calculus Volume 1 ↗ compared_alternative [CC BY-NC-SA 4.0]

Stable numbered text and exercises; retained alongside the lecture and recitation sequence.

Essence of Calculus ↗ compared_alternative [Copyright 3Blue1Brown / Grant Sanderson (no general open license)]

Visual motivation without an answer-keyed exercise sequence; retained for intuition.

linking CC BY-NC-SA 4.0 attribution noncommercial share-alike

OpenStax Calculus Volume 1

Author: OpenStax, Rice University (Gilbert Strang, Edwin Herman, et al.) | Original Source Link ↗

Relevant Section / Range: Sections 2.1-2.3 (Functions, Limits, and the Derivative); Sections 3.1-3.2 (Derivative Rules)

Verified Version & Date: 3rd edition, verified 2026-10-30

Selection Rationale:

Open, systematic treatment of the limit definition and derivative rules with stable section locations.

Source Prerequisites:

Algebra, coordinate geometry, and function notation

Safe Fallback (Offline Resilience):

The authored derivations, tables, and exercises in these three Study Days are complete offline recovery material; use the linked section only for optional comparison.

Compared Candidate Sources & Selection Analysis (3)
MIT OpenCourseWare 18.01SC Single Variable Calculus ↗ compared_selected_for_visual_practice [CC BY-NC-SA 4.0]

Strong exercises and transcripts, but the noncommercial share-alike terms and course navigation make OpenStax the primary stable text.

Paul's Online Math Notes: Calculus I ↗ compared_rejected_for_reuse [All Rights Reserved]

Useful reference, but rights and redistribution terms are less suitable for embedded recovery material.

SciPy Numerical Differentiation Documentation ↗ compared_selected_for_numerics [BSD-3-Clause]

A primary API reference for numerical derivative step-size behavior; it complements rather than replaces the hand derivation.

linking BSD-3-Clause

SciPy numerical derivative reference

Author: SciPy Developers | Original Source Link ↗

Relevant Section / Range: derivative API: finite differences, step-size iteration, tolerances

Verified Version & Date: SciPy documentation, verified 2026-10-30

Selection Rationale:

Documents numerical differentiation as an approximation with finite step sizes and stopping criteria.

Source Prerequisites:

Python arithmetic and the definition of a derivative

Safe Fallback (Offline Resilience):

The local Day 18 tables and pure-Python snippets reproduce the relevant finite-difference behavior without SciPy.

Compared Candidate Sources & Selection Analysis (2)
NumPy: numpy.gradient ↗ compared_alternative [BSD 3-Clause License]

Array-oriented gradient estimation on sampled grids; the SciPy derivative reference matches the pointwise finite-difference helper the exercises implement.

SymPy Calculus tutorial ↗ compared_alternative [BSD License]

Symbolic rather than numerical differentiation; useful for exact cross-checks but not the finite-difference practice target.

02 120 min

Rules with assumptions and a worked polynomial

Independent Mastery Check (no AI assistance).

Prerequisites

Complete the previous activity and use the listed recovery source if blocked.

Learning Objective

Apply constant, power, sum, and scalar-multiple rules to a polynomial while retaining the domain assumption that the expression is real-valued and differentiable at the evaluation point.

Instructions

1. List the rules you may use and what each needs: constant rule (d/dx c = 0), power rule (d/dx x^n = n x^(n-1)), constant-multiple rule, sum and difference rules. Each needs every term to be differentiable at the point.
2. Split q(x) = x^3 - 2x + 1 into its three terms and differentiate one term at a time, naming the rule on each line.
3. Keep the coefficient and lower the exponent by one: -2x is -2 x^1, so its derivative is -2 x^0 = -2.
4. Assemble q'(x), then substitute x = 2 with brackets: 3(2)^2 - 2.
5. Check the result with a central difference at h = 0.001, by hand or with a calculator.
6. Repeat the routine on the practice items before looking at the worked answer.

Time plan (120 min): reading 25 + exercise 65 + check 30. Reading: OpenStax Sections 3.2-3.3 (the derivative as a function, differentiation rules). Exercise: items (a)-(c) and the numerical check. Check: the mastery item on r(x), unaided, with every rule named.

Practice & Prediction Log

(a) For q(x)=x^3-2x+1, derive q'(x), then calculate q'(2). Show each term's derivative and the numerical substitution. (b) Find every x where q'(x)=0. (c) Differentiate u(x)=2x^5-3x^2+7x and evaluate u'(1). Check (a) with a central difference at h=0.001.

Independent Mastery Criterion

Without assistance, differentiate r(x)=4x^3+x^2-5 and evaluate r'(1)=14, showing the rule used for every term.

Authoritative Source Resources & Provenance

linking CC BY-NC-SA 4.0 attribution noncommercial share-alike

OpenStax Calculus Volume 1

Author: OpenStax, Rice University (Gilbert Strang, Edwin Herman, et al.) | Original Source Link ↗

Relevant Section / Range: Sections 2.1-2.3 (Functions, Limits, and the Derivative); Sections 3.1-3.2 (Derivative Rules)

Verified Version & Date: 3rd edition, verified 2026-10-30

Selection Rationale:

Open, systematic treatment of the limit definition and derivative rules with stable section locations.

Source Prerequisites:

Algebra, coordinate geometry, and function notation

Safe Fallback (Offline Resilience):

The authored derivations, tables, and exercises in these three Study Days are complete offline recovery material; use the linked section only for optional comparison.

Compared Candidate Sources & Selection Analysis (3)
MIT OpenCourseWare 18.01SC Single Variable Calculus ↗ compared_selected_for_visual_practice [CC BY-NC-SA 4.0]

Strong exercises and transcripts, but the noncommercial share-alike terms and course navigation make OpenStax the primary stable text.

Paul's Online Math Notes: Calculus I ↗ compared_rejected_for_reuse [All Rights Reserved]

Useful reference, but rights and redistribution terms are less suitable for embedded recovery material.

SciPy Numerical Differentiation Documentation ↗ compared_selected_for_numerics [BSD-3-Clause]

A primary API reference for numerical derivative step-size behavior; it complements rather than replaces the hand derivation.

linking BSD-3-Clause

SciPy numerical derivative reference

Author: SciPy Developers | Original Source Link ↗

Relevant Section / Range: derivative API: finite differences, step-size iteration, tolerances

Verified Version & Date: SciPy documentation, verified 2026-10-30

Selection Rationale:

Documents numerical differentiation as an approximation with finite step sizes and stopping criteria.

Source Prerequisites:

Python arithmetic and the definition of a derivative

Safe Fallback (Offline Resilience):

The local Day 18 tables and pure-Python snippets reproduce the relevant finite-difference behavior without SciPy.

Compared Candidate Sources & Selection Analysis (2)
NumPy: numpy.gradient ↗ compared_alternative [BSD 3-Clause License]

Array-oriented gradient estimation on sampled grids; the SciPy derivative reference matches the pointwise finite-difference helper the exercises implement.

SymPy Calculus tutorial ↗ compared_alternative [BSD License]

Symbolic rather than numerical differentiation; useful for exact cross-checks but not the finite-difference practice target.

03 120 min

A nondifferentiable counterexample

Agent-Assisted Engineering Check

Prerequisites

Complete the previous activity and use the listed recovery source if blocked.

Learning Objective

Explain why v(x)=|x| is continuous at 0 but not differentiable there: its left-hand and right-hand difference quotients are -1 and +1, so no common two-sided derivative exists.

Instructions

1. Establish continuity first: |x| approaches 0 = v(0) from both sides, so v is continuous at 0. Continuity is necessary for a derivative, but not sufficient.
2. Write the difference quotient at 0: [v(0+h) - v(0)]/h = |h|/h.
3. Split by the sign of h: for positive h, |h| = h; for negative h, |h| = -h. Never write |h| = h for negative h.
4. Evaluate each case at h = 0.1 and h = -0.1, then state each one-sided limit.
5. Conclude: a derivative exists only if both one-sided limits exist and are equal.
6. Apply the same test to the practice functions; one of them is differentiable at 0, and one has a quotient that grows without bound.

Time plan (120 min): reading 25 + exercise 60 + check 35. Reading: OpenStax Section 3.2 (differentiability and continuity: corners and vertical tangents). Exercise: items (a)-(c). Check: write the independent explanation the mastery criterion asks for, then compare.

Practice & Prediction Log

(a) Compute [v(0+h)-v(0)]/h separately for h>0 and h<0. Use h=.1 and h=-.1 as checks, then generalize. (b) Is w(x)=x|x| differentiable at 0? Use the same quotient. (c) For c(x)=x^(1/3) (the real cube root), compute the quotient at 0 for h=0.001 and h=-0.001, and say what happens as h approaches 0.

Independent Mastery Criterion

Independent explanation must include continuity at 0, both one-sided quotient values, and the conclusion 'not differentiable at 0' rather than merely saying 'corner.'

Authoritative Source Resources & Provenance

linking CC BY-NC-SA 4.0 attribution noncommercial share-alike

OpenStax Calculus Volume 1

Author: OpenStax, Rice University (Gilbert Strang, Edwin Herman, et al.) | Original Source Link ↗

Relevant Section / Range: Sections 2.1-2.3 (Functions, Limits, and the Derivative); Sections 3.1-3.2 (Derivative Rules)

Verified Version & Date: 3rd edition, verified 2026-10-30

Selection Rationale:

Open, systematic treatment of the limit definition and derivative rules with stable section locations.

Source Prerequisites:

Algebra, coordinate geometry, and function notation

Safe Fallback (Offline Resilience):

The authored derivations, tables, and exercises in these three Study Days are complete offline recovery material; use the linked section only for optional comparison.

Compared Candidate Sources & Selection Analysis (3)
MIT OpenCourseWare 18.01SC Single Variable Calculus ↗ compared_selected_for_visual_practice [CC BY-NC-SA 4.0]

Strong exercises and transcripts, but the noncommercial share-alike terms and course navigation make OpenStax the primary stable text.

Paul's Online Math Notes: Calculus I ↗ compared_rejected_for_reuse [All Rights Reserved]

Useful reference, but rights and redistribution terms are less suitable for embedded recovery material.

SciPy Numerical Differentiation Documentation ↗ compared_selected_for_numerics [BSD-3-Clause]

A primary API reference for numerical derivative step-size behavior; it complements rather than replaces the hand derivation.

linking BSD-3-Clause

SciPy numerical derivative reference

Author: SciPy Developers | Original Source Link ↗

Relevant Section / Range: derivative API: finite differences, step-size iteration, tolerances

Verified Version & Date: SciPy documentation, verified 2026-10-30

Selection Rationale:

Documents numerical differentiation as an approximation with finite step sizes and stopping criteria.

Source Prerequisites:

Python arithmetic and the definition of a derivative

Safe Fallback (Offline Resilience):

The local Day 18 tables and pure-Python snippets reproduce the relevant finite-difference behavior without SciPy.

Compared Candidate Sources & Selection Analysis (2)
NumPy: numpy.gradient ↗ compared_alternative [BSD 3-Clause License]

Array-oriented gradient estimation on sampled grids; the SciPy derivative reference matches the pointwise finite-difference helper the exercises implement.

SymPy Calculus tutorial ↗ compared_alternative [BSD License]

Symbolic rather than numerical differentiation; useful for exact cross-checks but not the finite-difference practice target.

04 120 min

Retrieval, derivative meaning, and mastery

Independent Mastery Check (no AI assistance)

Prerequisites

Complete the previous activity and use the listed recovery source if blocked.

Learning Objective

Retrieve limit, derivative, slope, and nondifferentiability ideas and use them to interpret a derivative as a local linear approximation, with honest independent evidence.

Instructions

1. Closed book: write an answer to every part before you open notes, earlier answers or AI tools.
2. Differentiate s with the rules, naming each one, then confirm s'(3) from the limit definition: expand s(3+h), subtract s(3), divide by h.
3. Compute s(3) before writing the tangent line; a tangent line needs a point and a slope.
4. Write the tangent in point-slope form, convert it to y = mx + b, and check it at x = 3.
5. Use the tangent as a local linear approximation at x = 3.1 and compare it with the true s(3.1).
6. For |x| at 0, write both one-sided difference quotients as limits with their values, then state the conclusion in one sentence.
7. Mark your attempt against the reference. For each miss, revisit Activity 1, 2 or 3 and redo an equivalent item (for example, s at x = 1) unaided.

Time plan (120 min): reading 15 + exercise 60 + check 45. Reading: only your notes from Activities 1-3. Exercise: the full closed-book prompt plus the linear approximation. Check: mark, revisit, and solve the x=1 variant unaided.

Practice & Prediction Log

Closed book: for s(x)=x^2-4x, find s'(x), s'(3), and the full tangent-line equation at x=3 (a slope alone is insufficient). Then contrast s with |x| at 0 in two sentences, including BOTH one-sided difference quotients lim(h->0+) and lim(h->0-) for |x|.

Independent Mastery Criterion

Independent Mastery Check: no AI, derive s'(3) from the limit definition or clearly apply justified rules, write the tangent line, and give the |x| counterexample with both one-sided quotients.

Authoritative Source Resources & Provenance

linking CC BY-NC-SA 4.0 attribution noncommercial share-alike

OpenStax Calculus Volume 1

Author: OpenStax, Rice University (Gilbert Strang, Edwin Herman, et al.) | Original Source Link ↗

Relevant Section / Range: Sections 2.1-2.3 (Functions, Limits, and the Derivative); Sections 3.1-3.2 (Derivative Rules)

Verified Version & Date: 3rd edition, verified 2026-10-30

Selection Rationale:

Open, systematic treatment of the limit definition and derivative rules with stable section locations.

Source Prerequisites:

Algebra, coordinate geometry, and function notation

Safe Fallback (Offline Resilience):

The authored derivations, tables, and exercises in these three Study Days are complete offline recovery material; use the linked section only for optional comparison.

Compared Candidate Sources & Selection Analysis (3)
MIT OpenCourseWare 18.01SC Single Variable Calculus ↗ compared_selected_for_visual_practice [CC BY-NC-SA 4.0]

Strong exercises and transcripts, but the noncommercial share-alike terms and course navigation make OpenStax the primary stable text.

Paul's Online Math Notes: Calculus I ↗ compared_rejected_for_reuse [All Rights Reserved]

Useful reference, but rights and redistribution terms are less suitable for embedded recovery material.

SciPy Numerical Differentiation Documentation ↗ compared_selected_for_numerics [BSD-3-Clause]

A primary API reference for numerical derivative step-size behavior; it complements rather than replaces the hand derivation.

linking BSD-3-Clause

SciPy numerical derivative reference

Author: SciPy Developers | Original Source Link ↗

Relevant Section / Range: derivative API: finite differences, step-size iteration, tolerances

Verified Version & Date: SciPy documentation, verified 2026-10-30

Selection Rationale:

Documents numerical differentiation as an approximation with finite step sizes and stopping criteria.

Source Prerequisites:

Python arithmetic and the definition of a derivative

Safe Fallback (Offline Resilience):

The local Day 18 tables and pure-Python snippets reproduce the relevant finite-difference behavior without SciPy.

Compared Candidate Sources & Selection Analysis (2)
NumPy: numpy.gradient ↗ compared_alternative [BSD 3-Clause License]

Array-oriented gradient estimation on sampled grids; the SciPy derivative reference matches the pointwise finite-difference helper the exercises implement.

SymPy Calculus tutorial ↗ compared_alternative [BSD License]

Symbolic rather than numerical differentiation; useful for exact cross-checks but not the finite-difference practice target.