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B3.2 · Identify exponential growth and decay models and contextual restrictions

Learn to identify exponential growth and decay models and contextual restrictions through clear examples and targeted practice.

Ontario Grade 11 Mathematics

Exponential Functions

Identifying Models and Understanding Contextual Restrictions

You have already worked with exponential functions in the form f(x)=a⋅bxf(x) = a \cdot b^x in Grade 10. You know that these functions change by a constant multiplicative factor, not a constant additive one. In this lesson you will take that foundation and use it to identify real-world situations that follow exponential growth or decay patterns. You will also learn how the context of a problem creates restrictions — limits on what values of the input and output actually make sense. By the end of this lesson you will be able to look at a situation or an equation and confidently say whether it represents growth or decay, and precisely describe the values that are meaningful in that context.

What you will learn

Prerequisite Bridge: What Makes a Function Exponential?

Recall from Grade 10 that a function is exponential when the input variable appears in the exponent. The general form is f(x)=a⋅bxf(x) = a \cdot b^x, where aa is the starting value (the output when x=0x = 0) and bb is the base, a fixed number that controls how quickly the function changes.
Two conditions must both be true for the function to be exponential: the base bb must be a positive real number, and bb must not equal 11. If b=1b = 1, then bx=1b^x = 1 for every xx, which gives a constant function, not an exponential one.
One key property: every time xx increases by 11, the output is multiplied by bb. This constant multiplication is what separates exponential change from linear change, where the output changes by a constant addition instead.
f(x)=a⋅bxf(x) = a \cdot b^x

Growth vs. Decay: Reading the Base

The base bb is the single most important number for identifying the type of exponential behaviour. When b>1b > 1, each step multiplies the output by a number greater than one, so the output gets larger over time. This is called exponential growth. A classic example is a population that doubles every year: the base would be 22.
When 0<b<10 < b < 1, each step multiplies the output by a fraction, so the output shrinks over time. This is called exponential decay. A classic example is a radioactive substance that loses half its mass every hour: the base would be 0.50.5.
It is also common to write the model using a rate of change rr rather than the base directly. If a quantity grows by a percentage rate rr each period, you can write the base as b=1+rb = 1 + r. If it decays by a rate rr each period, the base is b=1−rb = 1 - r. For instance, a 20% growth rate gives b=1.20b = 1.20, and a 15% decay rate gives b=0.85b = 0.85. Both forms, a⋅bxa \cdot b^x and a(1+r)xa(1+r)^x or a(1−r)xa(1-r)^x, describe exactly the same exponential model.
A useful memory check: growth bases sit above 11 on the number line; decay bases sit between 00 and 11. Bases outside the range (0,1)∪(1,∞)(0, 1) \cup (1, \infty) — that is, negative numbers, zero, or exactly 11 — do not produce valid exponential functions.
b>1 (growth),0<b<1 (decay)b > 1 \text{ (growth)}, 0 < b < 1 \text{ (decay)}

Contextual Restrictions on Domain and Range

Mathematically, the function f(x)=a⋅bxf(x) = a \cdot b^x is defined for every real number xx. But in a real situation, not every xx-value and not every output value makes physical sense. The set of input values that make sense is called the contextual domain, and the set of meaningful output values is called the contextual range.
Consider a model for the number of bacteria in a lab sample. Time cannot be negative if you are measuring from the moment the experiment starts, so x≥0x \geq 0. The number of bacteria must be a whole number and must be at least one to start. These constraints come from the real world, not from algebra. They restrict both the domain and the range even though the underlying function is defined more broadly.
Consider a model for the value of a car after purchase. Years driven cannot be negative, giving x≥0x \geq 0. The car's value cannot be negative either, so the range is restricted to non-negative values. Also, you would not expect to keep tracking a car's value past the point where it reaches zero, so the domain has a practical upper bound too.
Always ask three questions when finding contextual restrictions: Can the input be negative? Does the input have a natural stopping point? Can the output be zero or negative in this context? Your answers shape the restricted domain and range.

Identifying Growth and Decay from Descriptions and Equations

When a problem gives you an equation, look straight at the base. Extract the value of bb and decide whether it is greater than 11 (growth) or between 00 and 11 (decay). If the equation is written with a rate, compute 1+r1 + r or 1−r1 - r and do the same check.
When a problem gives you a description, look for key language. Words such as 'doubles', 'triples', 'increases by a percentage', or 'grows at a rate of' signal growth. Words such as 'halves', 'decays', 'depreciates', 'decreases by a percentage', or 'loses a fraction' signal decay.
A table of values can also reveal exponential behaviour: calculate the ratio of consecutive outputs. If the ratio is constant (the same number every time), the relationship is exponential. A ratio greater than 11 means growth; a ratio between 00 and 11 means decay. This is different from a linear relationship, where the differences between consecutive outputs are constant, not the ratios.
Once you identify the type, always state the restrictions. A complete answer names the model (growth or decay), identifies aa and bb, and states the contextual domain and range.

Growth vs. Decay at a Glance

FeatureExponential GrowthExponential Decay
Condition on baseb>1b > 10<b<10 < b < 1
Output behaviourIncreases as xx increasesDecreases as xx increases
Written with rate r>0r > 0b=1+rb = 1 + rb=1−rb = 1 - r
Typical languagedoubles, triples, grows by %halves, depreciates, loses %
Example baseb=1.25b = 1.25 (25% growth rate)b=0.75b = 0.75 (25% decay rate)

Worked example

Identifying a Decay Model and Its Restrictions

A used car is purchased for CAD 24 000. Its value decreases by 18% each year. Write an exponential model for the car's value VV after tt years, identify whether it represents growth or decay, and state the contextual domain and range.
  1. Write down what you know
    The initial value is CAD 24 000, so a=24000a = 24000. The car loses 18% of its value each year, meaning it keeps 100%−18%=82%100\% - 18\% = 82\% of its value each year. The base is therefore b=1−0.18=0.82b = 1 - 0.18 = 0.82.
    a=24000,b=1−0.18=0.82a = 24000, b = 1 - 0.18 = 0.82
  2. Write the model
    Substitute a=24000a = 24000 and b=0.82b = 0.82 into the general form V(t)=a⋅btV(t) = a \cdot b^t.
    V(t)=24000⋅(0.82)tV(t) = 24000 · (0.82)^t
  3. Identify growth or decay
    Because the base b=0.82b = 0.82 satisfies 0<0.82<10 < 0.82 < 1, each year the value is multiplied by a number less than one. The output shrinks over time, so this is an exponential decay model.
    0<0.82<1⇒decay0 < 0.82 < 1 \Rightarrow \text{decay}
  4. State the contextual domain
    Time tt represents years after purchase. You cannot have negative years in this context, so t≥0t \geq 0. Practically, you might stop tracking once the car's value becomes negligible, but a clear lower bound is t=0t = 0. The contextual domain is t≥0t \geq 0, or in set notation \{t ∈ R\mathbb{R} \mid t ≥ 0\}.
    t≥0t ≥ 0
  5. State the contextual range
    At t=0t = 0, the value is CAD 24 000. As tt increases the value decreases toward zero but can never actually reach zero (mathematically). In context, car value cannot be negative, so the range is 0<V(t)≤240000 < V(t) \leq 24000, measured in dollars.
    0<V(t)≤240000 < V(t) ≤ 24000
Answer: V(t)=24000⋅(0.82)tV(t) = 24000 \cdot (0.82)^t is an exponential decay model. Contextual domain: t≥0t \geq 0. Contextual range: 0<V(t)≤240000 < V(t) \leq 24000.
Check: At t=1t = 1: V(1)=24000×0.82=19680V(1) = 24000 \times 0.82 = 19680. A loss of CAD 4320 is exactly 18% of CAD 24000, confirming the model is correct.

Worked example

Identifying a Growth Model from a Table of Values

A biologist records the number of yeast cells in a culture every hour. The counts are: at hour 00, there are 500 cells; at hour 11, there are 1500 cells; at hour 22, there are 4500 cells; at hour 33, there are 13500 cells. Determine whether this is an exponential growth or decay model, write its equation P(t)P(t), and state the contextual restrictions.
  1. Check for a constant ratio
    Divide each output by the previous output to see whether the ratio is constant. From hour 0 to hour 1: 1500÷500=31500 \div 500 = 3. From hour 1 to hour 2: 4500÷1500=34500 \div 1500 = 3. From hour 2 to hour 3: 13500÷4500=313500 \div 4500 = 3. The ratio is constantly 33, confirming exponential behaviour.
    1500500=45001500=135004500=3\frac{1500}{500} = \frac{4500}{1500} = \frac{13500}{4500} = 3
  2. Identify a and b
    The initial value at t=0t = 0 is a=500a = 500. The constant ratio is the base, so b=3b = 3.
    a=500,b=3a = 500, b = 3
  3. Write the model
    Substitute a=500a = 500 and b=3b = 3 into P(t)=a⋅btP(t) = a \cdot b^t.
    P(t)=500⋅3tP(t) = 500 · 3^t
  4. Identify growth or decay
    The base b=3b = 3 is greater than 11, so each hour the population is multiplied by 33. The output grows over time. This is an exponential growth model.
    b=3>1⇒growthb = 3 > 1 \Rightarrow \text{growth}
  5. State the contextual domain and range
    Time tt cannot be negative in this experiment, so the domain is t≥0t \geq 0. The number of cells must be a positive whole number; the smallest meaningful value is 500 (at t=0t = 0). So the range is P(t)≥500P(t) \geq 500. There is also a practical upper limit because a lab culture has finite space and nutrients, but based on the information given, we state P(t)≥500P(t) \geq 500.
    t≥0,P(t)≥500t ≥ 0, P(t) ≥ 500
Answer: P(t)=500⋅3tP(t) = 500 \cdot 3^t is an exponential growth model. Contextual domain: t≥0t \geq 0. Contextual range: P(t)≥500P(t) \geq 500.
Check: At t=3t = 3: P(3)=500×33=500×27=13500P(3) = 500 \times 3^3 = 500 \times 27 = 13500. This matches the table value, confirming the model is correct.

Common mistakes and how to avoid them

Thinking a negative base, such as b=−2b = -2, produces a valid exponential function.
Correction: The base must satisfy b>0b > 0 and b≠1b \neq 1. A negative base causes the output to alternate between positive and negative values, which is not exponential behaviour.
Confusing the growth rate rr with the base bb. For example, a 20% growth rate leads some students to write b=0.20b = 0.20.
Correction: The base is b=1+r=1+0.20=1.20b = 1 + r = 1 + 0.20 = 1.20, not 0.200.20. The 11 accounts for the quantity that was already there before growth occurred.
Forgetting contextual restrictions and stating the domain as all real numbers for a time-based model.
Correction: Time cannot be negative in most real contexts, so the domain should be restricted to t≥0t \geq 0 unless the problem explicitly involves time before a reference point.
Using the differences between consecutive table values instead of the ratios to decide between linear and exponential behaviour.
Correction: For exponential models, the ratios of consecutive outputs are constant. For linear models, the differences are constant. Always divide consecutive outputs to test for exponential behaviour.
Stating b=1b = 1 is valid because 1x=11^x = 1 is technically defined.
Correction: Although 1x1^x is defined, it produces a constant function equal to aa, not an exponential function. The definition of an exponential function requires b≠1b \neq 1.

Lesson summary

Check your understanding

Question 1

A function is given by f(t)=800⋅(0.6)tf(t) = 800 \cdot (0.6)^t. Which statement correctly identifies this function?
  1. Exponential growth, because the initial value 800 is positive.
  2. Exponential decay, because the base 0.6 satisfies 0<0.6<10 < 0.6 < 1.
  3. Exponential growth, because the exponent tt increases.
  4. Neither growth nor decay, because the base is less than 1 and therefore invalid.
Show answer and explanation
Exponential decay, because the base 0.6 satisfies 0<0.6<10 < 0.6 < 1.
The type of model is determined by the base, not by the initial value or the exponent alone. Since 0<0.6<10 < 0.6 < 1, each step multiplies the output by a number less than one, causing the output to shrink. This is exponential decay. A base between 0 and 1 is perfectly valid for an exponential function.

Question 2

A savings account earns 4% interest per year, compounded annually, and starts with CAD 1000. What is the correct base of the exponential model for its value?
  1. b=0.04b = 0.04
  2. b=0.96b = 0.96
  3. b=1.04b = 1.04
  4. b=4b = 4
Show answer and explanation
b=1.04b = 1.04
A 4% growth rate means the account keeps 100% of its current value and adds 4% more each year. The base is b=1+0.04=1.04b = 1 + 0.04 = 1.04. The option b=0.04b = 0.04 confuses the rate with the base; b=0.96b = 0.96 is the decay base for a 4% loss; and b=4b = 4 would represent a 300% growth rate, which is far too large.

Question 3

A model tracks the mass of a melting ice block starting at time t=0t = 0. Which contextual restriction is most appropriate for the range of this model?
  1. The range is all real numbers, since the mathematical function is defined everywhere.
  2. The range is restricted to M(t)>0M(t) > 0, because mass cannot be zero or negative.
  3. The range is restricted to M(t)≥1M(t) \geq 1, because the block must always have at least 1 kg remaining.
  4. The range is restricted to M(t)<0M(t) < 0, because the block is losing mass.
Show answer and explanation
The range is restricted to M(t)>0M(t) > 0, because mass cannot be zero or negative.
Mass cannot be negative in any real context. Mathematically, an exponential decay function approaches zero but never reaches it, so the mass stays positive. The contextual range is therefore M(t)>0M(t) > 0. There is no physical reason to require at least 1 kg, and negative mass is impossible.

Question 4

A table shows outputs of 4, 12, 36, and 108 for inputs x=0,1,2,3x = 0, 1, 2, 3. What does this tell you?
  1. The relationship is linear, because the outputs keep increasing.
  2. The relationship is exponential decay with base b=3b = 3.
  3. The relationship is exponential growth with base b=3b = 3, and the initial value is a=4a = 4.
  4. The relationship is exponential growth with base b=4b = 4, because the first output is 4.
Show answer and explanation
The relationship is exponential growth with base b=3b = 3, and the initial value is a=4a = 4.
Divide consecutive outputs: 12÷4=312 \div 4 = 3, 36÷12=336 \div 12 = 3, 108÷36=3108 \div 36 = 3. The constant ratio of 33 confirms exponential behaviour. Because 3>13 > 1, this is growth, not decay. The initial value is the output at x=0x = 0, which is 44, not the ratio. The model is f(x)=4⋅3xf(x) = 4 \cdot 3^x.

Key terms

Exponential function
A function of the form f(x)=a⋅bxf(x) = a \cdot b^x where the variable xx appears in the exponent, a≠0a \neq 0, b>0b > 0, and b≠1b \neq 1.
Initial value (aa)
The output of an exponential function when the input is zero; it equals f(0)=a⋅b0=af(0) = a \cdot b^0 = a.
Base (bb)
The fixed number by which the output is multiplied for each unit increase in the input. It controls whether the function grows or decays.
Exponential growth
Exponential behaviour where the output increases over time, identified by a base b>1b > 1.
Exponential decay
Exponential behaviour where the output decreases over time, identified by a base satisfying 0<b<10 < b < 1.
Growth or decay rate (rr)
The percentage, written as a decimal, by which a quantity increases or decreases each period. The growth base is 1+r1 + r and the decay base is 1−r1 - r.
Contextual domain
The set of input values that make sense within the real-world situation being modelled, which may be narrower than the mathematical domain.
Contextual range
The set of output values that make sense within the real-world situation being modelled, which may be narrower than the mathematical range.

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Published by DoAssignment. This AI-assisted lesson follows Ontario Grade 11 Mathematics (MCR3U), expectation B3.2. It is a study resource, not an official curriculum publication.

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