OCR MEI AS Paper 1 2021 November — Question 11 10 marks

Exam BoardOCR MEI
ModuleAS Paper 1 (AS Paper 1)
Year2021
SessionNovember
Marks10
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicExponential Functions
TypeCompare or choose between models
DifficultyModerate -0.8 This is a straightforward modelling question requiring only basic linear algebra (simultaneous equations), substitution into an exponential function, and differentiation. All techniques are routine A-level methods with no problem-solving insight needed, making it easier than average but not trivial due to the multi-part structure.
Spec1.03a Straight lines: equation forms y=mx+c, ax+by+c=01.06a Exponential function: a^x and e^x graphs and properties1.06i Exponential growth/decay: in modelling context

11 On the day that a new consumer product went on sale (day zero), a call centre received 1 call about it. On the 2nd day after day zero the call centre received 3 calls, and on the 10th day after day zero there were 200 calls. Two models were proposed to model \(N\), the number of calls received \(t\) days after day zero.
Model 1 is a linear model \(\mathrm { N } = \mathrm { mt } + \mathrm { c }\).
  1. Determine the values of \(m\) and \(c\) which best model the data for 2 days and 10 days after day zero.
  2. State the rate of increase in calls according to model 1.
  3. Explain why this model is not suitable when \(t = 1\). Model 2 is an exponential model \(\mathbf { N } = e ^ { 0.53 t }\).
  4. Verify that this is a good model for the number of calls when \(t = 2\) and \(t = 10\).
  5. Determine the rate of increase in calls when \(t = 10\) according to model 2 .

Question 11:
Part (a):
Main Method:
Line joining \((2, 3)\) to \((10, 200)\) has gradient:
AnswerMarks Guidance
\(\frac{200-3}{10-2} = 24.625\)M1 (AO 3.3) Attempt to find the gradient of the line
\(m = \frac{197}{8} = 24.625\), \(c = -\frac{185}{4} = -46.25\)A1, A1 (AO 1.1, 1.1) Each value correct. Accept rounded to 2 or more s.f. Values may be implied by correct equation
Equation of the line is \(N = 24.625t - 46.25\)
Alternative Solution 1:
AnswerMarks Guidance
Regression line (BC) for data set \((2, 3)\), \((10, 200)\)M1 Using the calculator to find the regression line (may be implied)
Regression line is \(N = 24.625t - 46.25\)
AnswerMarks Guidance
\(m = 24.625\), \(c = -46.25\)A1, A1 Each value correct. Accept rounded to 2 or more s.f. Values may be implied by correct equation
Alternative Solution 2:
Simultaneous equations:
AnswerMarks Guidance
Using \((2, 3)\): \(2m + c = 3\) and using \((10, 200)\): \(10m + c = 200\)M1 Attempt to find and solve simultaneous equations (BC)
\(m = \frac{197}{8} = 24.625\), \(c = -\frac{185}{4} = -46.25\)A1, A1 Each value correct. Accept rounded to 2 or more s.f.
[3]
Part (b):
AnswerMarks Guidance
The number of calls increases by \(24.625\) per dayB1 (AO 3.4) FT their \(m\). Condone missing units
[1]
Part (c):
AnswerMarks Guidance
When \(t = 1\), \(N = -21.625\) and \(N\) cannot be negativeB1 (AO 3.5b) Argument from a correct value for \(N\). FT their equation
[1]
Part (d):
AnswerMarks Guidance
When \(t = 2\), \(N = e^{0.53 \times 2} = 2.886 \approx 3\)M1 (AO 1.1a) Substitution of both values into the model, soi
When \(t = 10\), \(N = e^{0.53 \times 10} = 200.33 \approx 200\)
AnswerMarks Guidance
So this is a good model for these two pointsE1 (AO 3.4) Conclusion from correct values
[2]
Part (e):
AnswerMarks Guidance
Rate of increase \(\frac{dN}{dt} = 0.53e^{0.53t}\)M1 (AO 1.1a) Using gradient of \(e^{kx} = ke^{kx}\)
When \(t = 10\), \(\frac{dN}{dt} = 0.53e^{0.53 \times 10}\)M1 (AO 1.1a) Substituting \(t = 10\) into their expression
\(106\) new calls per dayB1 (AO 3.4) cao Allow for gradient found BC or numerical method
[3]
## Question 11:

### Part (a):

**Main Method:**

Line joining $(2, 3)$ to $(10, 200)$ has gradient:

$\frac{200-3}{10-2} = 24.625$ | M1 (AO 3.3) | Attempt to find the gradient of the line

$m = \frac{197}{8} = 24.625$, $c = -\frac{185}{4} = -46.25$ | A1, A1 (AO 1.1, 1.1) | Each value correct. Accept rounded to 2 or more s.f. Values may be implied by correct equation

Equation of the line is $N = 24.625t - 46.25$

---

**Alternative Solution 1:**

Regression line (BC) for data set $(2, 3)$, $(10, 200)$ | M1 | Using the calculator to find the regression line (may be implied)

Regression line is $N = 24.625t - 46.25$

$m = 24.625$, $c = -46.25$ | A1, A1 | Each value correct. Accept rounded to 2 or more s.f. Values may be implied by correct equation

---

**Alternative Solution 2:**

Simultaneous equations:

Using $(2, 3)$: $2m + c = 3$ and using $(10, 200)$: $10m + c = 200$ | M1 | Attempt to find and solve simultaneous equations (BC)

$m = \frac{197}{8} = 24.625$, $c = -\frac{185}{4} = -46.25$ | A1, A1 | Each value correct. Accept rounded to 2 or more s.f.

**[3]**

---

### Part (b):

The number of calls increases by $24.625$ per day | B1 (AO 3.4) | FT their $m$. Condone missing units

**[1]**

---

### Part (c):

When $t = 1$, $N = -21.625$ and $N$ cannot be negative | B1 (AO 3.5b) | Argument from a correct value for $N$. FT their equation

**[1]**

---

### Part (d):

When $t = 2$, $N = e^{0.53 \times 2} = 2.886 \approx 3$ | M1 (AO 1.1a) | Substitution of both values into the model, soi

When $t = 10$, $N = e^{0.53 \times 10} = 200.33 \approx 200$

So this is a good model for these two points | E1 (AO 3.4) | Conclusion from correct values

**[2]**

---

### Part (e):

Rate of increase $\frac{dN}{dt} = 0.53e^{0.53t}$ | M1 (AO 1.1a) | Using gradient of $e^{kx} = ke^{kx}$

When $t = 10$, $\frac{dN}{dt} = 0.53e^{0.53 \times 10}$ | M1 (AO 1.1a) | Substituting $t = 10$ into their expression

$106$ new calls per day | B1 (AO 3.4) | cao Allow for gradient found BC or numerical method

**[3]**
11 On the day that a new consumer product went on sale (day zero), a call centre received 1 call about it. On the 2nd day after day zero the call centre received 3 calls, and on the 10th day after day zero there were 200 calls.

Two models were proposed to model $N$, the number of calls received $t$ days after day zero.\\
Model 1 is a linear model $\mathrm { N } = \mathrm { mt } + \mathrm { c }$.
\begin{enumerate}[label=(\alph*)]
\item Determine the values of $m$ and $c$ which best model the data for 2 days and 10 days after day zero.
\item State the rate of increase in calls according to model 1.
\item Explain why this model is not suitable when $t = 1$.

Model 2 is an exponential model $\mathbf { N } = e ^ { 0.53 t }$.
\item Verify that this is a good model for the number of calls when $t = 2$ and $t = 10$.
\item Determine the rate of increase in calls when $t = 10$ according to model 2 .
\end{enumerate}

\hfill \mbox{\textit{OCR MEI AS Paper 1 2021 Q11 [10]}}