Business Calculus Quiz: Logistic Growth Models
13 questions · exam conditions
0:00
Logistic Growth ModelsQuestion 1 of 13

A biotechnology company models the adoption of their new medical device using the logistic equation dPdt=0.08P(1200−P)\frac{dP}{dt} = 0.08P(1200 - P), where P(t)P(t) represents the number of hospitals using the device at time tt (in months). If the current adoption rate is 15 hospitals per month and there are currently 200 hospitals using the device, what will be the adoption rate when 800 hospitals are using the device?

25.6 hospitals per month, representing continued exponential-like growth in the early adoption phase
32.0 hospitals per month, representing the maximum possible adoption rate for this model
19.2 hospitals per month, representing slower growth as the market approaches saturation
12.8 hospitals per month, representing the declining growth rate in the late adoption phase
← Back to quizzes

Business Calculus Quiz

Business Calculus Quiz: Logistic Growth Models

Practice Logistic Growth Models in Business Calculus with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Logistic Growth Models, giving you a quick way to practice the rules, question types, and explanations that matter most for Business Calculus.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

All questions

Question 1

A biotechnology company models the adoption of their new medical device using the logistic equation dPdt=0.08P(1200−P)\frac{dP}{dt} = 0.08P(1200 - P), where P(t)P(t) represents the number of hospitals using the device at time tt (in months). If the current adoption rate is 15 hospitals per month and there are currently 200 hospitals using the device, what will be the adoption rate when 800 hospitals are using the device?

  1. 25.6 hospitals per month, representing continued exponential-like growth in the early adoption phase (correct answer)
  2. 32.0 hospitals per month, representing the maximum possible adoption rate for this model
  3. 19.2 hospitals per month, representing slower growth as the market approaches saturation
  4. 12.8 hospitals per month, representing the declining growth rate in the late adoption phase
Explanation: Using the logistic equation dPdt=0.08P(1200−P)\frac{dP}{dt} = 0.08P(1200 - P), we substitute P=800P = 800: dPdt=0.08(800)(1200−800)=0.08(800)(400)=25,600/1000=25.6\frac{dP}{dt} = 0.08(800)(1200 - 800) = 0.08(800)(400) = 25,600/1000 = 25.6 hospitals per month. Since 800 is still well below the carrying capacity of 1200, this represents continued strong growth. Choice B incorrectly assumes maximum rate occurs at P=800P = 800. Choice C uses the wrong calculation 0.08(800)(600/1200)0.08(800)(600/1200). Choice D incorrectly applies 0.08(200)(400/1200)0.08(200)(400/1200).

Question 2

The market penetration of a new mobile application, N(t) (in thousands of users), t months after launch, is modeled by the differential equation $$ \frac{dN}{dt} = 0.8N - 0.0002N^2 $$ What is the maximum rate of new user acquisition, in thousands of users per month?

  1. 4000
  2. 2000
  3. 800 (correct answer)
  4. 1600
Explanation: To find the maximum rate, we first need to identify the parameters of the logistic model, which is typically written as dN/dt = kN(1 - N/M). We can factor the given equation: dN/dt = 0.8N - 0.0002N^2 = 0.8N(1 - 0.0002N/0.8) = 0.8N(1 - N/4000). From this form, we identify the carrying capacity M = 4000 (thousand users). The rate of growth dN/dt is maximized at the point of inflection, which occurs when the population is half the carrying capacity, i.e., N = M/2 = 4000/2 = 2000. To find the maximum rate, we substitute N = 2000 back into the original differential equation: dN/dt = 0.8(2000) - 0.0002(2000)^2 = 1600 - 0.0002(4,000,000) = 1600 - 800 = 800. Thus, the maximum rate of new user acquisition is 800 thousand users per month.

Question 3

The proportion p(t) of a potential market that has adopted a new software is modeled by dp/dt = 0.3p(1-p). If 10% of the market has adopted the software at t=0, approximately how long will it take for 90% of the market to adopt it?

  1. 14.65 (correct answer)
  2. 7.33
  3. 9.77
  4. 4.88
Explanation: The differential equation dp/dt = 0.3p(1-p) is a logistic model for a proportion, where the carrying capacity M=1 (for 100%) and the growth constant k=0.3. The solution is p(t) = 1 / (1 + $Ae^{-0.3t}$). We use the initial condition p(0) = 0.1 to find A. A = (M - $p_0$) / p_0 = (1 - 0.1) / 0.1 = 9. So, p(t) = 1 / (1 + $9e^{-0.3t}$). We need to find t when p(t) = 0.9. 0.9 = 1 / (1 + $9e^{-0.3t}$). This gives 1 + 9e^{-0.3t} = 1/0.9 = 10/9. Then 9e^{-0.3t} = 10/9 - 1 = 1/9. So e^{-0.3t} = 1/81. Taking the natural log, -0.3t = \ln(1/81) = -\ln(81). Thus, t = \ln(81) / 0.3 \approx 4.3944 / 0.3 \approx 14.65.

Question 4

The sales S(t) of a new tablet, in millions of units, follow a logistic growth model. The total market for the tablet is estimated to be 20 million units. If the initial sales are 2 million units and the sales reach the point of maximum growth rate after 18 months, what is the value of the growth constant k?

  1. \ln(9) / 18 (correct answer)
  2. \ln(10) / 18
  3. \ln(18) / 9
  4. \ln(9) / 20
Explanation: The logistic model solution is S(t) = M / (1 + $Ae^{-kt}$). We are given M = 20 and S_0 = S(0) = 2. The constant A is found by A = (M - $S_0$) / S_0 = (20 - 2) / 2 = 9. The point of maximum growth rate occurs when the population is half the carrying capacity, S = M/2 = 20/2 = 10 million units. We are told this occurs at t=18 months. So, S(18) = 10. We plug this into the solution: 10 = 20 / (1 + $9e^{-k*18}$). Solving for k: 1 + 9e^{-18k} = 20/10 = 2. 9e^{-18k} = 1. e^{-18k} = 1/9. Taking the natural logarithm of both sides gives -18k = \ln(1/9) = -\ln(9). Therefore, 18k = \ln(9), and k = \ln(9) / 18.

Question 5

The number of active users U(t) for a mobile game t months after launch is modeled by dU/dt = 0.1U(1 - U/8), where U is in millions. The company earns an average of $2 in profit per user per month. At what number of active users is the company's total monthly profit increasing most rapidly?

  1. 8 million
  2. 2 million
  3. 4 million (correct answer)
  4. 0.4 million
Explanation: The monthly profit P is directly proportional to the number of users U, so P = 2U. We want to find when the profit is increasing most rapidly, which means we need to maximize the rate of change of profit, dP/dt. Using the chain rule, dP/dt = d(2U)/dt = 2 * (dU/dt). To maximize dP/dt, we must maximize dU/dt. The given differential equation for U(t) is a logistic model with carrying capacity M=8 million. The rate of growth dU/dt for a logistic model is at its maximum at the point of inflection, which occurs when the population is half the carrying capacity: U = M/2. Therefore, the profit increases most rapidly when U = 8/2 = 4 million users.

Question 6

The number of companies C(t) adopting a new sustainable technology follows a logistic model. The relative growth rate, (1/C) dC/dt, is 1.2 when 100 companies have adopted it, and the relative growth rate is 0.8 when 300 companies have adopted it. What is the maximum number of companies expected to adopt this technology?

  1. 500
  2. 600
  3. 700 (correct answer)
  4. 900
Explanation: For a logistic model dC/dt = kC(1 - C/M), the relative growth rate is (1/C) dC/dt = k(1 - C/M). We are given two data points: when C=100, the relative rate is 1.2, and when C=300, the relative rate is 0.8. This gives us a system of two linear equations with two unknowns, k and M: 1) 1.2 = k(1 - 100/M); 2) 0.8 = k(1 - 300/M). To solve this system, we can divide the first equation by the second: 1.2 / 0.8 = [k(1 - 100/M)] / [k(1 - 300/M)]. This simplifies to 1.5 = (1 - 100/M) / (1 - 300/M). Now, we solve for M: 1.5(1 - 300/M) = 1 - 100/M. 1.5 - 450/M = 1 - 100/M. 0.5 = 350/M. M = 350 / 0.5 = 700. The maximum number of companies is the carrying capacity, M.

Question 7

The spread of a viral marketing campaign is modeled by the logistic equation $$ \frac{dP}{dt} = 0.0001P(5000 - P) $$ where P(t) is the number of people who have seen the campaign after t days. If P(0) = 500, what is the value of P(t) when the rate of spread dP/dt is exactly 75% of its maximum possible value?

  1. 4226 or 774
  2. 3536 or 1464
  3. 2500
  4. 3750 or 1250 (correct answer)
Explanation: The carrying capacity is M = 5000. The maximum rate occurs at P = M/2 = 2500, where dP/dt = 0.0001(2500)(2500) = 625. We need 75% of this maximum: 0.75 × 625 = 468.75. Setting up the equation: 0.0001P(5000 - P) = 468.75, which gives P(5000 - P) = 4,687,500. Rearranging: P² - 5000P + 4,687,500 = 0. Using the quadratic formula: P = (5000 ± √(25,000,000 - 18,750,000))/2 = (5000 ± √6,250,000)/2 = (5000 ± 2500)/2. This gives P = 3750 or P = 1250.

Question 8

A subscription service models its user growth with dNdt=kN(M−N)\frac{dN}{dt} = kN(M - N) where M=80,000M = 80,000 is the market saturation. After analyzing growth patterns, they determine that when N=20,000N = 20,000, the growth rate is 1,200 users per month, and when N=60,000N = 60,000, the growth rate is 800 users per month. What is the value of the growth parameter kk?

  1. k=1.0×10−6k = 1.0 \times 10^{-6}, derived from the symmetric property of logistic growth (correct answer)
  2. k=1.5×10−6k = 1.5 \times 10^{-6}, calculated using the maximum growth rate condition
  3. k=2.0×10−6k = 2.0 \times 10^{-6}, obtained by averaging the two given growth scenarios
  4. k=0.5×10−6k = 0.5 \times 10^{-6}, determined from the early exponential growth approximation
Explanation: Using the first condition: 1200=k(20000)(80000−20000)=k(20000)(60000)=1.2×109k1200 = k(20000)(80000 - 20000) = k(20000)(60000) = 1.2 \times 10^9 k, so k=12001.2×109=1.0×10−6k = \frac{1200}{1.2 \times 10^9} = 1.0 \times 10^{-6}. Verification with second condition: k(60000)(80000−60000)=1.0×10−6(60000)(20000)=1200×60×2020×60=800k(60000)(80000 - 60000) = 1.0 \times 10^{-6}(60000)(20000) = 1200 \times \frac{60 \times 20}{20 \times 60} = 800 ✓. Choice B would give 1800 for the first condition. Choice C would give 2400 for the first condition. Choice D would give 600 for the first condition.

Question 9

A startup's user base grows according to P(t)=L1+e−k(t−t0)P(t) = \frac{L}{1 + e^{-k(t-t_0)}} where L=50000L = 50000, k=0.15k = 0.15, and t0=24t_0 = 24 months. The company's server costs are proportional to [P′(t)]2[P'(t)]^2. During which month will the server costs be highest, and what percentage of the carrying capacity will the user base represent at that time?

  1. Month 24 with user base at 50% of carrying capacity, representing optimal growth efficiency (correct answer)
  2. Month 20 with user base at 35% of carrying capacity, during maximum acceleration phase
  3. Month 28 with user base at 65% of carrying capacity, in the peak expansion period
  4. Month 30 with user base at 75% of carrying capacity, approaching market saturation
Explanation: Server costs are highest when [P′(t)]2[P'(t)]^2 is maximum, which occurs when ∣P′(t)∣|P'(t)| is maximum. For the logistic function, P′(t)P'(t) is maximum at the inflection point t=t0=24t = t_0 = 24 months. At this point, P(24)=500001+e−0.15(24−24)=500001+1=25000P(24) = \frac{50000}{1 + e^{-0.15(24-24)}} = \frac{50000}{1 + 1} = 25000, which is exactly 50% of the carrying capacity. Choice B incorrectly identifies an earlier time before peak growth rate. Choice C assumes peak occurs after the inflection point. Choice D confuses high user count with high growth rate, occurring well past the maximum derivative.

Question 10

The market share P(t) of a new product follows a logistic model. It is observed that the rate of change of the market share, dP/dt, is increasing for the first 3 years and then begins to decrease. The total potential market is estimated at 1 million customers. If the initial market share comprised 50,000 customers, which of the following is the best estimate for the number of customers at t=3 years?

  1. 250,000
  2. 1,000,000
  3. 750,000
  4. 500,000 (correct answer)
Explanation: In a logistic growth model, the rate of growth dP/dt increases until the population reaches the point of inflection, after which the rate of growth decreases. This point of maximum growth rate corresponds to the population being exactly half of the carrying capacity, P = M/2. The problem states that the rate of change increases for the first 3 years and then decreases, which means the point of inflection occurs at t=3 years. Given the total potential market (carrying capacity) M = 1,000,000 customers, the number of customers at the point of inflection is M/2 = 1,000,000 / 2 = 500,000. Therefore, at t=3 years, the market share is 500,000 customers. The initial condition of 50,000 customers is consistent with the model but not needed to find the answer.

Question 11

A new product's sales, S(t), in thousands of units, are modeled by a logistic differential equation where the carrying capacity is 500 thousand units and the growth constant is k=0.05. If the initial sales are 100 thousand units, at what sales level S is the acceleration of sales, d^2S/dt^2, equal to zero?

  1. 100 thousand units
  2. 250 thousand units (correct answer)
  3. 500 thousand units
  4. 300 thousand units
Explanation: When you encounter logistic growth problems asking about acceleration being zero, you're looking for the inflection point where the growth rate changes from increasing to decreasing. For a logistic model, S(t)=L1+Ae−ktS(t) = \frac{L}{1 + Ae^{-kt}} where LL is the carrying capacity. The second derivative d2Sdt2\frac{d^2S}{dt^2} equals zero at the inflection point, which always occurs at exactly half the carrying capacity. Here's why: The logistic curve is S-shaped, starting slow, accelerating through the middle, then slowing as it approaches the carrying capacity. The inflection point marks where acceleration stops and deceleration begins. Mathematically, this happens when S=L2S = \frac{L}{2}. Since your carrying capacity is 500 thousand units, the inflection point occurs at 5002=250\frac{500}{2} = 250 thousand units, making B correct. Looking at the wrong answers: A (100 thousand units) is the initial sales level, where acceleration is actually positive, not zero. C (500 thousand units) is the carrying capacity itself, where sales approach their maximum but acceleration has long since turned negative. D (300 thousand units) represents no special point in the logistic model - it's past the inflection point where acceleration is negative. Study tip: Remember that for any logistic growth model, the inflection point (where d2Sdt2=0\frac{d^2S}{dt^2} = 0) always occurs at exactly half the carrying capacity, regardless of the growth constant or initial conditions. This makes these problems much faster to solve.

Question 12

The total number of subscribers S(t) for a streaming service after t years is given by the logistic function $$ S(t) = \frac{150}{1 + 29e^{-0.75t}} $$ where S is in millions. The company's management considers the "rapid growth phase" to be over when the service reaches 80% of its total market capacity. Approximately how many years does the rapid growth phase last from its launch?

  1. 4.49 years
  2. 6.34 years (correct answer)
  3. 5.21 years
  4. 3.56 years
Explanation: From the logistic function S(t) = M / (1 + $Ae^{-kt}$), the carrying capacity (total market capacity) M is 150 million. The rapid growth phase ends when the number of subscribers reaches 80% of M, which is 0.80 * 150 = 120 million. We set S(t) = 120 and solve for t: 120 = 150 / (1 + $29e^{-0.75t}$). Rearranging gives 1 + 29e^{-0.75t} = 150/120 = 1.25. Then, 29e^{-0.75t} = 0.25, so e^{-0.75t} = 0.25/29. Taking the natural logarithm of both sides: -0.75t = \ln(0.25/29). Solving for t: t = -\ln(0.25/29) / 0.75 = \ln(29/0.25) / 0.75 = \ln(116) / 0.75 \approx 4.7536 / 0.75 \approx 6.34 years.

Question 13

An e-commerce platform's seller adoption follows dSdt=aS(b−S)\frac{dS}{dt} = aS(b - S) where S(t)S(t) is the number of active sellers. Market research indicates that when there are 1000 sellers, the platform adds 400 new sellers monthly, and when there are 3000 sellers, it adds 600 new sellers monthly. What is the carrying capacity bb?

  1. b=4000b = 4000 sellers, representing the maximum sustainable marketplace size for this platform
  2. b=5000b = 5000 sellers, indicating the theoretical upper limit based on market analysis (correct answer)
  3. b=6000b = 6000 sellers, corresponding to the platform's full market penetration potential
  4. b=3500b = 3500 sellers, reflecting the practical capacity given current growth constraints
Explanation: Using the logistic equation dSdt=aS(b−S)\frac{dS}{dt} = aS(b-S), we have two conditions: 400=a(1000)(b−1000)400 = a(1000)(b-1000) and 600=a(3000)(b−3000)600 = a(3000)(b-3000). From the first equation: a=4001000(b−1000)=0.4b−1000a = \frac{400}{1000(b-1000)} = \frac{0.4}{b-1000}. Substituting into the second: 600=0.4b−1000⋅3000(b−3000)=1200(b−3000)b−1000600 = \frac{0.4}{b-1000} \cdot 3000(b-3000) = \frac{1200(b-3000)}{b-1000}. Cross-multiplying: 600(b−1000)=1200(b−3000)600(b-1000) = 1200(b-3000), so 600b−600000=1200b−3600000600b - 600000 = 1200b - 3600000, giving 600b=3000000600b = 3000000, thus b=5000b = 5000. Choice A gives inconsistent growth rates when verified. Choice C would yield negative growth at S=3000S = 3000. Choice D fails the second growth condition.