AP Course

AP Calculus AB/BC

Study the complete College Board sequence for AP Calculus AB and BC, from limits through infinite series.

Choose an official unit and topic to open its lecture, concept check, or focused practice.

Lessons
1.1 Introducing Calculus: Can Change Occur at an Instant?1.2 Defining Limits and Using Limit Notation1.3 Estimating Limit Values from Graphs1.4 Estimating Limit Values from Tables1.5 Determining Limits Using Algebraic Properties of Limits1.6 Determining Limits Using Algebraic Manipulation1.7 Selecting Procedures for Determining Limits1.8 Determining Limits Using the Squeeze Theorem1.9 Connecting Multiple Representations of Limits1.10 Exploring Types of Discontinuities1.11 Defining Continuity at a Point1.12 Confirming Continuity over an Interval1.13 Removing Discontinuities1.14 Connecting Infinite Limits and Vertical Asymptotes1.15 Connecting Limits at Infinity and Horizontal Asymptotes1.16 Working with the Intermediate Value Theorem (IVT)2.1 Defining Average and Instantaneous Rates of Change at a Point2.2 Defining the Derivative of a Function and Using Derivative Notation2.3 Estimating Derivatives of a Function at a Point2.4 Connecting Differentiability and Continuity: Determining When Derivatives Do and Do Not Exist2.5 Applying the Power Rule2.6 Derivative Rules: Constant, Sum, Difference, and Constant Multiple2.7 Derivatives of cos x, sin x, e^x, and ln x2.8 The Product Rule2.9 The Quotient Rule2.10 Finding the Derivatives of Tangent, Cotangent, Secant, and/or Cosecant Functions3.1 The Chain Rule3.2 Implicit Differentiation3.3 Differentiating Inverse Functions3.4 Differentiating Inverse Trigonometric Functions3.5 Selecting Procedures for Calculating Derivatives3.6 Calculating Higher-Order Derivatives4.1 Interpreting the Meaning of the Derivative in Context4.2 Straight-Line Motion: Connecting Position, Velocity, and Acceleration4.3 Rates of Change in Applied Contexts Other Than Motion4.4 Introduction to Related Rates4.5 Solving Related Rates Problems4.6 Approximating Values of a Function Using Local Linearity and Linearization4.7 Using L’Hospital’s Rule for Determining Limits of Indeterminate Forms5.1 Using the Mean Value Theorem5.2 Extreme Value Theorem, Global Versus Local Extrema, and Critical Points5.3 Determining Intervals on Which a Function Is Increasing or Decreasing5.4 Using the First Derivative Test to Determine Relative (Local) Extrema5.5 Using the Candidates Test to Determine Absolute (Global) Extrema5.6 Determining Concavity of Functions over Their Domains5.7 Using the Second Derivative Test to Determine Extrema5.8 Sketching Graphs of Functions and Their Derivatives5.9 Connecting a Function, Its First Derivative, and Its Second Derivative5.10 Introduction to Optimization Problems5.11 Solving Optimization Problems5.12 Exploring Behaviors of Implicit Relations6.1 Exploring Accumulations of Change6.2 Approximating Areas with Riemann Sums6.3 Riemann Sums, Summation Notation, and Definite Integral Notation6.4 The Fundamental Theorem of Calculus and Accumulation Functions6.5 Interpreting the Behavior of Accumulation Functions Involving Area6.6 Applying Properties of Definite Integrals6.7 The Fundamental Theorem of Calculus and Definite Integrals6.8 Finding Antiderivatives and Indefinite Integrals: Basic Rules and Notation6.9 Integrating Using Substitution6.10 Integrating Functions Using Long Division and Completing the Square6.11 Integrating Using Integration by Parts6.12 Using Linear Partial Fractions6.13 Evaluating Improper Integrals6.14 Selecting Techniques for Antidifferentiation7.1 Modeling Situations with Differential Equations7.2 Verifying Solutions for Differential Equations7.3 Sketching Slope Fields7.4 Reasoning Using Slope Fields7.5 Approximating Solutions Using Euler’s Method7.6 Finding General Solutions Using Separation of Variables7.7 Finding Particular Solutions Using Initial Conditions and Separation of Variables7.8 Exponential Models with Differential Equations7.9 Logistic Models with Differential Equations8.1 Finding the Average Value of a Function on an Interval8.2 Connecting Position, Velocity, and Acceleration of Functions Using Integrals8.3 Using Accumulation Functions and Definite Integrals in Applied Contexts8.4 Finding the Area Between Curves Expressed as Functions of x8.5 Finding the Area Between Curves Expressed as Functions of y8.6 Finding the Area Between Curves That Intersect at More Than Two Points8.7 Volumes with Cross Sections: Squares and Rectangles8.8 Volumes with Cross Sections: Triangles and Semicircles8.9 Volume with Disc Method: Revolving Around the x- or y-Axis8.10 Volume with Disc Method: Revolving Around Other Axes8.11 Volume with Washer Method: Revolving Around the x- or y-Axis8.12 Volume with Washer Method: Revolving Around Other Axes8.13 The Arc Length of a Smooth, Planar Curve and Distance Traveled9.1 Defining and Differentiating Parametric Equations9.2 Second Derivatives of Parametric Equations9.3 Finding Arc Lengths of Curves Given by Parametric Equations9.4 Defining and Differentiating Vector-Valued Functions9.5 Integrating Vector-Valued Functions9.6 Solving Motion Problems Using Parametric and Vector-Valued Functions9.7 Defining Polar Coordinates and Differentiating in Polar Form9.8 Find the Area of a Polar Region or the Area Bounded by a Single Polar Curve9.9 Finding the Area of the Region Bounded by Two Polar Curves10.1 Defining Convergent and Divergent Infinite Series10.2 Working with Geometric Series10.3 The nth Term Test for Divergence10.4 Integral Test for Convergence10.5 Harmonic Series and p-Series10.6 Comparison Tests for Convergence10.7 Alternating Series Test for Convergence10.8 Ratio Test for Convergence10.9 Determining Absolute or Conditional Convergence10.10 Alternating Series Error Bound10.11 Finding Taylor Polynomial Approximations of Functions10.12 Lagrange Error Bound10.13 Radius and Interval of Convergence of Power Series10.14 Finding Taylor or Maclaurin Series for a Function10.15 Representing Functions as Power Series
Quizzes
Practice Problems AP formula notes, graph references, and practice sets will be added here.

AP Calculus AB/BC · Unit 7 · Topic 7.1

Modeling Situations with Differential Equations

Write an equation that relates a quantity's rate to current variables and parameters.

1. Topic Focus

Model rates with differential equations, read slope fields, approximate solutions, solve separable equations, and interpret exponential or logistic models.

This topic: Write an equation that relates a quantity's rate to current variables and parameters.

2. Key Relationship

\(\frac{dy}{dt}=F(t,y)\)

Read every symbol with its domain, direction, units, and hypotheses before applying the relationship.

3. Visual Connection

ratecontextDEy'=Fchecky and y'
Model and verificationTranslate units and rate language into an equation, then substitute the proposed function and initial value.

4. Worked Example

A population growing proportionally to its size satisfies dP/dt=kP.

Write the governing relationship first, carry out the algebra cleanly, and finish with a sentence that answers the mathematical question.

5. Concept Development

A differential equation turns a description of change into a mathematical rate law. If \(Q(t)\) is the quantity being modeled, a first-order model has the form

\(\frac{dQ}{dt}=F(t,Q).\)

The left side is a rate, so every term on the right must have the same rate units. The initial condition \(Q(t_0)=Q_0\) is separate from the differential equation: the equation describes a family of possible behaviors, while the initial value identifies the behavior that fits the situation.

A reliable modeling workflow

  1. Name the variables and units. State what \(t\) measures and what the dependent variable represents.
  2. Identify parameters. Record which constants are positive and attach units when useful.
  3. Build the net rate. Use “rate in minus rate out” or “production minus loss.”
  4. Translate each verbal relationship. For example, “proportional to the amount” becomes \(kQ\).
  5. Add initial data. Write \(Q(t_0)=Q_0\) if a starting value is given.
  6. Audit the model. Check units, signs, equilibria, physical restrictions, and the interval on which the assumptions are reasonable.

Common verbal cues

DescriptionRate modelInterpretation
increases at a constant rate \(r\)\(Q'=r\)the same amount is added per unit time
decreases at a constant rate \(r\)\(Q'=-r\)\(r>0\) is the magnitude of the loss
changes proportionally to its amount\(Q'=kQ\)growth if \(k>0\), decay if \(k<0\)
moves toward a level \(M\)\(Q'=k(M-Q)\)the sign automatically points toward \(M\)
input and output occur together\(Q'=R_{\mathrm{in}}-R_{\mathrm{out}}\)convert both terms to quantity per time
growth is limited by capacity \(K\)\(P'=rP(1-P/K)\)growth slows as \(P\) approaches \(K\)

Units, signs, and equilibria

In \(P'=kP\), if \(t\) is measured in years, then \(k\) has units \(\text{year}^{-1}\). In \(T'=-k(T-A)\), the same reciprocal-time units for \(k\) make both sides temperature per time. An equilibrium is a constant value \(Q=Q_*\) for which the modeled rate is zero. Values on either side of an equilibrium reveal whether solutions move toward it or away from it.

An equation such as \(Q'=F(Q)\) is autonomous: its rate depends on the current state but not explicitly on time. A model such as \(Q'=4+\sin t-0.1Q\) is nonautonomous because its input varies with time.

Model assumptions matter

A model is an approximation, not the situation itself. A mixing model may assume a perfectly stirred tank and constant volume; a cooling model may assume constant ambient temperature; a population model may ignore migration or changing resources. State restrictions such as \(Q\ge 0\), and stop using a model when its assumptions produce physically impossible predictions.

Topic focus: Topic 7.1 asks you to formulate and interpret the differential equation. Solving separable, exponential, or logistic equations is developed later in Unit 7.

6. Detailed Worked Example and Error Check

Example 1: Population with constant harvesting

A population \(P(t)\) has a per-capita birth rate of \(0.18\) per year and a per-capita death rate of \(0.07\) per year. A fixed \(120\) individuals are removed each year, and \(P(0)=2500\).

\(\frac{dP}{dt}=0.18P-0.07P-120=0.11P-120,\qquad P(0)=2500.\)

Every term has units individuals per year. The equilibrium is \(P=120/0.11\approx1091\). Above it the model predicts growth; below it the fixed harvest exceeds natural net growth. Because the formula could eventually predict a negative population, its physical use must stop at \(P=0\).

Example 2: Newton's law of cooling

A hot object at \(90^\circ\mathrm C\) is placed in a room held at \(22^\circ\mathrm C\). Its temperature changes at a rate proportional to the difference from the room temperature.

\(\frac{dT}{dt}=-k(T-22)=k(22-T),\qquad T(0)=90,\quad k>0.\)

When \(T>22\), the derivative is negative; if \(T<22\), it is positive. Thus the sign of the model always moves the temperature toward \(22\), which is its equilibrium.

Example 3: A well-mixed tank

A \(200\)-liter tank contains \(S(t)\) grams of salt. Brine enters and leaves at \(3\) liters per minute, so volume remains constant. The incoming concentration is \(2\) grams per liter.

\(\begin{aligned}R_{\mathrm{in}}&=(3\ \mathrm{L/min})(2\ \mathrm{g/L})=6\ \mathrm{g/min},\\R_{\mathrm{out}}&=(3\ \mathrm{L/min})\left(\frac{S}{200}\ \mathrm{g/L}\right)=\frac{3S}{200}\ \mathrm{g/min},\\[2pt]\frac{dS}{dt}&=6-\frac{3S}{200}.\end{aligned}\)

The outflow concentration is \(S/200\), not simply \(S\). Setting \(S'=0\) gives the equilibrium \(S=400\) grams, the amount corresponding to the incoming concentration throughout the tank.

Example 4: Medication infusion

A medicine enters a patient's bloodstream at \(5\) milligrams per hour and is eliminated at a rate proportional to the amount \(M(t)\), with proportionality constant \(0.12\) per hour.

\(M'=5-0.12M.\)

The equilibrium amount is \(5/0.12\approx41.7\) milligrams. If \(M\) is below that level, the net rate is positive; above it, elimination is faster than infusion.

Example 5: Time-dependent input

Water enters a reservoir at \(8+2\sin(\pi t/12)\) cubic meters per hour and leaves at \(5\) cubic meters per hour. If \(V(0)=300\), then

\(V'=3+2\sin\left(\frac{\pi t}{12}\right),\qquad V(0)=300.\)

This model is nonautonomous because the inflow depends explicitly on time. The derivative, rather than \(V\), equals the net flow.

Example 6: Limited population growth

A population has intrinsic growth constant \(0.4\) per year and carrying capacity \(500\). A standard logistic model is

\(P'=0.4P\left(1-\frac{P}{500}\right),\qquad P(0)=80.\)

The factors identify equilibria \(P=0\) and \(P=500\). For \(0<P<500\), both factors are positive, so the population grows; above \(500\), the model predicts a decrease.

Example 7: Motion with linear resistance

Take downward velocity \(v(t)\) as positive. Gravity contributes acceleration \(g\), while resistance of magnitude \(kv\) acts upward when the object is falling.

\(\frac{dv}{dt}=g-kv,\qquad v(0)=0,\quad k>0.\)

The equilibrium velocity \(v=g/k\) is the terminal velocity. Choosing the positive direction first prevents a sign guess from replacing physical reasoning.

Common modeling errors

  • Equating an amount to a rate, such as \(S=6-3S/200\).
  • Using inflow concentration as an inflow rate without multiplying by volume per time.
  • Writing \(T'=-k|T-A|\), which incorrectly predicts cooling even when \(T<A\).
  • Omitting the initial condition or hiding a parameter's required sign.
  • Solving an equation before checking whether it represents the verbal situation.

7. AP Reasoning Routine

Translate the context into a rate equation, verify candidate solutions by substitution, carry constants through integration, and apply initial conditions last.

  • Identify the representation and requested quantity.
  • State the rule or theorem and verify its conditions.
  • Keep exact values until the final requested approximation.
  • Interpret sign, units, interval, and context.
AP Checkpoint

Write a differential equation and any stated initial condition for each situation. Define positive constants when needed, but do not solve the equations.
(a) A lake loses \(15\) cubic meters of water per day.
(b) A culture begins with \(600\) cells and grows at a rate proportional to its current population.
(c) An object at \(20^\circ\mathrm C\) is heated in an oven held at \(180^\circ\mathrm C\), with rate proportional to the temperature difference.
(d) A medication enters at \(8\) milligrams per hour and \(20\%\) of the current amount is eliminated per hour. Find the equilibrium and describe the sign of the rate on each side.
(e) A well-mixed \(100\)-liter tank receives and drains \(4\) liters per minute. Incoming brine contains \(0.5\) gram per liter. Let \(S(t)\) be salt in grams.
(f) A population has carrying capacity \(1200\) and intrinsic growth constant \(0.3\) per year.
(g) A falling object's downward velocity is positive. Gravity contributes \(g\), and air resistance produces acceleration of magnitude \(kv\) opposite the motion. The object is released from rest.
(h) If \(N'=kN\) and \(t\) is measured in days, what units must \(k\) have?
(i) Explain why \(T'=-k|T-20|\), \(k>0\), is not an appropriate model for an object warming from \(5^\circ\mathrm C\) toward a \(20^\circ\mathrm C\) room.
(j) A tank receives liquid at \(4+t\) liters per minute and drains at a rate equal to \(Q/50\) liters per minute, where \(Q(t)\) is its volume and \(Q(0)=100\).

Check the solution

(a) If \(V\) is volume, \(V'=-15\).
(b) \(P'=kP\), \(P(0)=600\), with \(k>0\).
(c) \(T'=k(180-T)\), \(T(0)=20\), with \(k>0\). The derivative is positive below the oven temperature.
(d) \(M'=8-0.20M\). The equilibrium is \(M=40\) milligrams; \(M'>0\) below \(40\) and \(M'<0\) above \(40\).
(e) Inflow is \((4)(0.5)=2\) grams per minute and outflow is \(4(S/100)=S/25\), so \(S'=2-S/25\).
(f) \(P'=0.3P(1-P/1200)\).
(g) \(v'=g-kv\), \(v(0)=0\), with \(k>0\).
(h) Since \(N'\) has units amount per day, \(k\) must have units \(\text{day}^{-1}\).
(i) At \(T=5\), the proposed right side is negative, so it predicts further cooling. A model that points toward room temperature is \(T'=k(20-T)\).
(j) Net rate equals inflow minus outflow: \(Q'=4+t-Q/50\), \(Q(0)=100\). This is nonautonomous because the inflow varies with \(t\).