OCR H240/01 2023 June — Question 11 12 marks

Exam BoardOCR
ModuleH240/01 (Pure Mathematics)
Year2023
SessionJune
Marks12
PaperDownload PDF ↗
TopicExponential Functions
TypeLinear transformation to find constants
DifficultyModerate -0.3 This is a standard A-level question on exponential models using logarithmic linearization. Part (a) requires recognizing that a straight line on a log-linear plot confirms exponential growth. Part (b) involves checking that log₁₀(120) ≈ 2.08 and log₁₀(1.15) matches the gradient. Parts (c-d) are routine substitution and solving exponential equations. While multi-part, each step follows textbook procedures with no novel problem-solving required, making it slightly easier than average.
Spec1.06h Logarithmic graphs: reduce y=ax^n and y=kb^x to linear form1.06i Exponential growth/decay: in modelling context

11 The owners of an online shop believe that their sales can be modelled by \(S = a b ^ { t }\), where \(a\) and \(b\) are both positive constants, \(S\) is the number of items sold in a month and \(t\) is the number of complete months since starting their online shop. The sales for the first six months are recorded, and the values of \(\log _ { 10 } S\) are plotted against \(t\) in the graph below. The graph is repeated in the Printed Answer Booklet. \includegraphics[max width=\textwidth, alt={}, center]{9473b8f7-616a-485e-963b-696c6640ae6b-08_1203_1408_552_244}
  1. Explain why the graph suggests that the given model is appropriate. The owners believe that \(a = 120\) and \(b = 1.15\) are good estimates for the parameters in the model.
  2. Show that the graph supports these estimates for the parameters.
  3. Use the model \(S = 120 \times 1.15 ^ { t }\) to predict the number of items sold in the seventh month after opening.
    1. Use the model \(S = 120 \times 1.15 ^ { t }\) to predict the number of months after opening when the total number of items sold after opening will first exceed 70000 .
    2. Comment on how reliable this prediction may be.

Question 11:
Part (a):
AnswerMarks Guidance
AnswerMarks Guidance
\(\log_{10}S = \log_{10}(ab^t)\); \(\log_{10}S = \log_{10}a + \log_{10}b^t\)M1 Attempt to show reduction to linear form. Introduce logs on both sides and correctly split to sum of two terms
\(\log_{10}S = t\log_{10}b + \log_{10}a\)A1 Obtain correct equation. Condone no base. A0 for \(\log_{10}bt\) unless previously seen as \(t\log_{10}b\)
which is of the form \(Y = mX + c\)A1 Link to equation of straight line
Alternative method:
AnswerMarks Guidance
AnswerMarks Guidance
\(\log_{10}S = mt + c\); \(S = 10^{mt+c}\)M1 Attempt equation of straight line and attempt expression for \(S\). Must use \(\log_{10}S\) against \(t\), base 10
\(S = 10^{mt} \times 10^c\)A1 Correctly split into two terms
which is of the form \(S = ab^t\)A1 Link to exponential model
Question 11(b):
AnswerMarks Guidance
\(m = \log_{10}b = 0.06\) so \(b = 10^{0.06} = 1.15\)B1 Link gradient of line of best fit to linear form and confirm \(b \approx 1.15\); allow \(m\) in range \([0.055, 0.065]\); or \(\log_{10}1.15 = 0.06\) and compare to gradient
\(c = \log_{10}a = 2.08\) so \(a = 10^{2.08} = 120\)B1 Link intercept of line of best fit to linear form and confirm \(a \approx 120\); allow \(c\) in range \([2.075, 2.085]\); or \(\log_{10}120 = 2.08\) and compare to intercept
[2]
Question 11(c):
AnswerMarks Guidance
\(S = 120 \times 1.15^7\)M1 Substitute \(t = 7\) into given model; soi
predicted sales are 319 itemsA1 Conclude with integer value; accept 320 items
[2]
Question 11(d)(i):
AnswerMarks Guidance
GP with \(a = 138\) and \(r = 1.15\)B1 State or imply sum of GP with \(a\) as 120 or 138, and \(r\) as 1.15; could be implied by attempt to use GP sum formula
\(\dfrac{138(1-1.15^t)}{1-1.15} = 70000\)M1\* Attempt sum of GP with \(a = 120\) or 138 and \(r = 1.15\), related to 70000; must be correct sum formula; may have \(n\) not \(t\) throughout
\(1.15^t = 77.087\)M1 dep\* Attempt to rearrange equation as far as \(1.15^t =\); must now have \(a = 138\); allow sign errors only; allow T&I as not DR
\(t = 31.088\ldots\) hence 32 monthsA1 Obtain 32 ('months not required'); if 32 given as answer only then allow full marks
[4]
Question 11(d)(ii):
AnswerMarks Guidance
Unlikely to be reliable as sales may not continue in same pattern as market could become saturatedB1 State or imply that the model is unlikely to be valid, with a sensible reason; e.g. decrease in demand, increase in competition, no values beyond \(t=6\) so pattern unknown, sales likely to level off, other factors, seasonal variation
[1]
# Question 11:

## Part (a):
| Answer | Marks | Guidance |
|--------|-------|----------|
| $\log_{10}S = \log_{10}(ab^t)$; $\log_{10}S = \log_{10}a + \log_{10}b^t$ | **M1** | Attempt to show reduction to linear form. Introduce logs on both sides and correctly split to sum of two terms |
| $\log_{10}S = t\log_{10}b + \log_{10}a$ | **A1** | Obtain correct equation. Condone no base. A0 for $\log_{10}bt$ unless previously seen as $t\log_{10}b$ |
| which is of the form $Y = mX + c$ | **A1** | Link to equation of straight line |

**Alternative method:**
| Answer | Marks | Guidance |
|--------|-------|----------|
| $\log_{10}S = mt + c$; $S = 10^{mt+c}$ | **M1** | Attempt equation of straight line and attempt expression for $S$. Must use $\log_{10}S$ against $t$, base 10 |
| $S = 10^{mt} \times 10^c$ | **A1** | Correctly split into two terms |
| which is of the form $S = ab^t$ | **A1** | Link to exponential model |

## Question 11(b):

$m = \log_{10}b = 0.06$ so $b = 10^{0.06} = 1.15$ | **B1** | Link gradient of line of best fit to linear form and confirm $b \approx 1.15$; allow $m$ in range $[0.055, 0.065]$; or $\log_{10}1.15 = 0.06$ and compare to gradient

$c = \log_{10}a = 2.08$ so $a = 10^{2.08} = 120$ | **B1** | Link intercept of line of best fit to linear form and confirm $a \approx 120$; allow $c$ in range $[2.075, 2.085]$; or $\log_{10}120 = 2.08$ and compare to intercept

**[2]**

---

## Question 11(c):

$S = 120 \times 1.15^7$ | **M1** | Substitute $t = 7$ into given model; soi

predicted sales are 319 items | **A1** | Conclude with integer value; accept 320 items

**[2]**

---

## Question 11(d)(i):

GP with $a = 138$ and $r = 1.15$ | **B1** | State or imply sum of GP with $a$ as 120 or 138, and $r$ as 1.15; could be implied by attempt to use GP sum formula

$\dfrac{138(1-1.15^t)}{1-1.15} = 70000$ | **M1\*** | Attempt sum of GP with $a = 120$ or 138 and $r = 1.15$, related to 70000; must be correct sum formula; may have $n$ not $t$ throughout

$1.15^t = 77.087$ | **M1 dep\*** | Attempt to rearrange equation as far as $1.15^t =$; must now have $a = 138$; allow sign errors only; allow T&I as not DR

$t = 31.088\ldots$ hence 32 months | **A1** | Obtain 32 ('months not required'); if 32 given as **answer only** then allow full marks

**[4]**

---

## Question 11(d)(ii):

Unlikely to be reliable as sales may not continue in same pattern as market could become saturated | **B1** | State or imply that the model is unlikely to be valid, with a sensible reason; e.g. decrease in demand, increase in competition, no values beyond $t=6$ so pattern unknown, sales likely to level off, other factors, seasonal variation

**[1]**

---
11 The owners of an online shop believe that their sales can be modelled by $S = a b ^ { t }$, where $a$ and $b$ are both positive constants, $S$ is the number of items sold in a month and $t$ is the number of complete months since starting their online shop.

The sales for the first six months are recorded, and the values of $\log _ { 10 } S$ are plotted against $t$ in the graph below. The graph is repeated in the Printed Answer Booklet.\\
\includegraphics[max width=\textwidth, alt={}, center]{9473b8f7-616a-485e-963b-696c6640ae6b-08_1203_1408_552_244}
\begin{enumerate}[label=(\alph*)]
\item Explain why the graph suggests that the given model is appropriate.

The owners believe that $a = 120$ and $b = 1.15$ are good estimates for the parameters in the model.
\item Show that the graph supports these estimates for the parameters.
\item Use the model $S = 120 \times 1.15 ^ { t }$ to predict the number of items sold in the seventh month after opening.
\item \begin{enumerate}[label=(\roman*)]
\item Use the model $S = 120 \times 1.15 ^ { t }$ to predict the number of months after opening when the total number of items sold after opening will first exceed 70000 .
\item Comment on how reliable this prediction may be.
\end{enumerate}\end{enumerate}

\hfill \mbox{\textit{OCR H240/01 2023 Q11 [12]}}