Mathematics Advanced • Year 11 • Module 4 • Lesson 2

Graphs of Exponential Functions

Apply transformations and equation-from-features techniques to real and abstract contexts.

Apply · Problem Set

Problem 1 — Cooling coffee (vertical translation)

A cup of coffee cools in a room at 20°C. Its temperature is modelled by

T(t) = 70 · (0.9)t + 20,    t in minutes, T in °C

Set up: What are we solving for?

(i) State the asymptote of the T-graph and interpret it physically.   2 marks

(ii) Find T(0) and T(5) (1 d.p.). What temperature did the coffee start at?   2 marks

(iii) Sketch the temperature graph for 0 ≤ t ≤ 30, showing the asymptote, the y-intercept, and the value at t = 5. State the long-run temperature.   3 marks

Stuck? Revisit lesson § Worked Example 2 (translation example).

Problem 2 — Fish population (find equation from data)

A new fish species is introduced to a lake. The population (in thousands) measured each year is modelled by y = a · bx. The data shows:

Year xPopulation y (thousands)
05
220

Set up: What are we solving for?

(i) Use the (0, 5) data point to find a.   1 mark

(ii) Use the (2, 20) data point to find b (show one line of working).   2 marks

(iii) Use the model to predict the population at year 5. State your assumption (one sentence) about validity of the model for years beyond the data.   2 marks

Problem 3 — Drug clearance (decay graph)

A 200 mg dose of a drug is absorbed instantly. The amount in the bloodstream is modelled by

D(t) = 200 · (0.7)t,    t in hours

Set up: What are we solving for?

(i) Sketch D(t) for 0 ≤ t ≤ 8, showing the asymptote and y-intercept.   2 marks

(ii) Compute D(2), D(4), D(8) to the nearest milligram. By what factor does the dose decrease each hour, and by what factor over a 2-hour gap?   3 marks

(iii) A clinician says a "therapeutic threshold" is 50 mg. Use your sketch (or trial values) to estimate the largest whole number of hours t for which D(t) ≥ 50 mg.   2 marks

Stuck on (iii)? Calculate D(3), D(4), D(5) and find when it drops below 50.

Problem 4 — Pure transformations

Use the base graph y = 2x to describe each transformed graph below.

Set up: What are we solving for?

(i) Describe (in words, in order) the sequence of transformations that maps y = 2x onto y = −2x + 1 + 3.   3 marks

(ii) State the asymptote, y-intercept and range of y = −2x + 1 + 3.   3 marks

(iii) Explain in one sentence why the reflection in the x-axis turns "growth" behaviour (y > 0 for all x) into y < 0 for all x.   1 mark

Problem 5 — Comparing growth and decay graphs

The graphs of y = 2x and y = 2−x are drawn on the same axes.

Set up: What are we solving for?

(i) Show algebraically that y = 2−x is identical to y = (1/2)x.   1 mark

(ii) State the geometric relationship between the two graphs, and explain why this is so (one sentence using "reflection").   2 marks

(iii) Find their single point of intersection by setting 2x = 2−x. Show one line of working.   2 marks

Stuck on (iii)? Equal bases ⇒ equal exponents: x = −x.

How did this worksheet feel?

What I'll revisit before next class:

Answers — Do not peek before attempting

Problem 1 — Cooling coffee

Set up. Read the asymptote, compute initial and intermediate values, sketch and interpret the long-run behaviour.

(i) Asymptote: T = 20°C. Physically, this is the room (ambient) temperature; the coffee cools toward room temperature, never below it.

(ii) T(0) = 70 · 1 + 20 = 90°C (the initial temperature).   T(5) = 70 · (0.9)5 + 20 = 70 · 0.59049 + 20 ≈ 41.3 + 20 = 61.3°C.

(iii) Sketch: dashed asymptote T = 20, y-intercept (0, 90), curve decreasing through (5, 61.3) and approaching T = 20 from above. Long-run temperature: 20°C (the asymptote).

Problem 2 — Fish population

Set up. Fit y = a · bx to two data points to find both parameters.

(i) At (0, 5): 5 = a · b0 = a, so a = 5.

(ii) At (2, 20): 20 = 5 · b2 ⇒ b2 = 4 ⇒ b = 2 (positive root). Model: y = 5 · 2x.

(iii) y(5) = 5 · 25 = 5 · 32 = 160 (thousand fish). Assumption: the lake has sufficient food/space for the exponential trend to continue — in reality the population will be limited by carrying capacity and the model will overpredict for large x.

Problem 3 — Drug clearance

Set up. Sketch and read off decay values from D(t) = 200 · (0.7)t.

(i) Sketch: asymptote D = 0, y-intercept (0, 200), decreasing curve approaching the t-axis.

(ii) D(2) = 200 · 0.49 = 98 mg.   D(4) = 200 · 0.2401 ≈ 48 mg.   D(8) = 200 · 0.05765 ≈ 12 mg. Per hour the dose is multiplied by 0.7 (a 30% drop each hour). Over a 2-hour gap, by 0.72 = 0.49 (a 51% drop).

(iii) D(3) = 200 · 0.343 ≈ 69 mg (≥ 50).   D(4) ≈ 48 mg (< 50). Largest whole-number t with D(t) ≥ 50 is t = 3 hours.

Problem 4 — Transformations

Set up. Decompose a multi-transform expression into ordered single transformations and read off graph features.

(i) In order: (1) shift left 1 (x + 1 inside the exponent); (2) reflect in the x-axis (the negative sign in front); (3) shift up 3.

(ii) Asymptote: y = 3 (from the +3 outside). y-int at x = 0: y = −21 + 3 = −2 + 3 = 1; point (0, 1). Range: y < 3 (the reflection sends the original y > 0 to y < 0; adding 3 shifts to y < 3).

(iii) Reflecting in the x-axis multiplies every y-value by −1; since y = 2x > 0 for all x, the reflected y = −2x < 0 for all x.

Problem 5 — Growth vs decay graphs

Set up. Show two equivalent forms, describe the geometric symmetry, and find the intersection algebraically.

(i) 2−x = (2−1)x = (1/2)x. ✓

(ii) The graphs are reflections of each other in the y-axis. Replacing x by −x reflects every point (x, y) to (−x, y).

(iii) 2x = 2−x ⇒ x = −x ⇒ 2x = 0 ⇒ x = 0. At x = 0: y = 20 = 1. Intersection: (0, 1) — the common y-intercept.