| Exam Board | AQA |
|---|---|
| Module | S1 (Statistics 1) |
| Year | 2012 |
| Session | January |
| Marks | 17 |
| Paper | Download PDF ↗ |
| Mark scheme | Download PDF ↗ |
| Topic | Linear regression |
| Type | Calculate y on x from raw data table |
| Difficulty | Moderate -0.8 This is a standard S1 linear regression question requiring routine calculations (finding regression equation, making predictions, calculating residuals) and straightforward interpretations. All techniques are textbook exercises with no novel problem-solving required, though the multi-part structure and context-based interpretations make it slightly more substantial than pure recall. |
| Spec | 5.09a Dependent/independent variables5.09b Least squares regression: concepts5.09c Calculate regression line5.09d Linear coding: effect on regression |
| \(\boldsymbol { x }\) | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | 55 | 60 | 65 |
| \(\boldsymbol { y }\) | 5.2 | 4.7 | 4.3 | 4.0 | 3.2 | 2.8 | 2.5 | 2.2 | 1.8 | 1.5 | 1.3 | 1.0 | 0.6 |
| Answer | Marks | Guidance |
|---|---|---|
| Calorific value depends upon moisture content; Moisture (content) is set/are fixed values | B1 | 1 |
| Answer | Marks | Guidance |
|---|---|---|
| \(b \text{ (gradient)} = -0.076\) | B2 (B1) |
| Answer | Marks | Guidance |
|---|---|---|
| \(a \text{ (intercept)} = 5.35\) to \(5.36\) | B2 (B1) |
| Answer | Marks | Guidance |
|---|---|---|
| Thus \(y = (5.35 \text{ to } 5.36) - 0.076x\) | BF1 | 5 |
| Answer | Marks | Guidance |
|---|---|---|
| Attempt at \(\sum x\), \(\sum x^2\), \(\sum y\) & \(\sum xy\) \((\sum y^2)\) or Attempt at \(S_{xx}\) & \(S_{xy}\) \((S_{yy})\) | M1 | |
| Attempt at correct formula for \(b\) (gradient); \(b \text{ (gradient)} = -0.076\); \(a \text{ (intercept)} = 5.35\) to \(5.36\); Thus \(y = (5.35 \text{ to } 5.36) - 0.076x\) | m1, A1, A1, BF1 | 5 |
| Answer | Marks | Guidance |
|---|---|---|
| \(a\): calorific value of wood with zero/no moisture or dry maximum calorific value | B1 | |
| \(b\): each \(1(\%)\) rise in moisture content reduces calorific value by \(0.076\) MWh/tonne | B2 | 3 |
| As \(x\) increases \(y\) decreases | (B1) |
| Answer | Marks | Guidance |
|---|---|---|
| \(y_{27} = 3.28\) to \(3.32\) | B2 | 2 |
| \(= 2.5\) to \(3.5\) | (B1) |
| Answer | Marks | Guidance |
|---|---|---|
| \(y_{27} = (5.35 \text{ to } 5.36) - 0.076 \times 27\) | M1 | |
| \(= 3.28\) to \(3.32\) | A1 | 2 |
| Answer | Marks | Guidance |
|---|---|---|
| \(r(35, 2.5) = -0.21\) to \(-0.19\) | B2 | 2 |
| \(= 0.1\) to \(0.3\) | (B1) |
| Answer | Marks | Guidance |
|---|---|---|
| \(r(35, 2.5) = 2.5 - y_{35}\) | M1 | |
| \(= 2.5 - \{(5.35 \text{ to } 5.36) - 0.076 \times 35\}\) | ||
| \(= -0.21\) to \(-0.19\) | A1 | 2 |
| Answer | Marks | Guidance |
|---|---|---|
| Good/reasonable/accurate/correct/etc; Accept more positive qualifying adjectives | B1 | 1 |
| Answer | Marks | Guidance |
|---|---|---|
| Extrapolation/outside (observed) range (of \(x\)) | B1 | 1 |
| Answer | Marks | Guidance |
|---|---|---|
| \(y_{80} = -0.5\) to \(-1\) | B1 | |
| Negative value for calorific value is impossible OR More energy needed than is generated | Bdep1 | 2 |
# Question 5:
## Part (a):
Calorific value depends upon moisture content; Moisture (content) is set/are fixed values | B1 | 1 | Must be in context; **not** "it", etc. Use of $x$ and $y \Rightarrow$ B0
## Part (b):
$b \text{ (gradient)} = -0.076$ | B2 (B1) | | AWRT; including $-$ve sign $(-0.07582)$; AWFW; including $-$ve sign; Treat rounding of correct answers as ISW
$b \text{ (gradient)} = -0.07$ to $-0.08$
$a \text{ (intercept)} = 5.35$ to $5.36$ | B2 (B1) | | AWFW (5.35385); AWFW
$a \text{ (intercept)} = 5.1$ to $5.6$
Thus $y = (5.35 \text{ to } 5.36) - 0.076x$ | BF1 | 5 | F on $a$ and $b$ even if rounded
**Alternative solutions:**
Attempt at $\sum x$, $\sum x^2$, $\sum y$ & $\sum xy$ $(\sum y^2)$ or Attempt at $S_{xx}$ & $S_{xy}$ $(S_{yy})$ | M1 | | 455, 20475, 35.1 & 883.5 (121.33) (all 4 attempted); 4550 & $-345$ (26.56) (both attempted)
Attempt at correct formula for $b$ (gradient); $b \text{ (gradient)} = -0.076$; $a \text{ (intercept)} = 5.35$ to $5.36$; Thus $y = (5.35 \text{ to } 5.36) - 0.076x$ | m1, A1, A1, BF1 | 5 | AWRT; AWFW; F on $a$ and $b$ even if rounded
Notes: **1** If $a$ and $b$ interchanged and equation $y = ax + b$ used $\Rightarrow$ max of 5 marks; **2** If $a$ and $b$ interchanged and equation $y = a + bx$ used $\Rightarrow$ maximum of BF1; **3** Marks lost here cannot be gained from subsequent work in parts (d) and/or (e)
## Part (c):
$a$: calorific value of wood with zero/no moisture or dry maximum calorific value | B1 | | OE; $a \leq 0 \Rightarrow$ B0
$b$: each $1(\%)$ rise in moisture content reduces calorific value by $0.076$ MWh/tonne | B2 | 3 | In context and with values; F on $b$; $b \geq 0 \Rightarrow$ B0
As $x$ increases $y$ decreases | (B1) | | Negative relationship/correlation
## Part (d):
$y_{27} = 3.28$ to $3.32$ | B2 | 2 | AWFW (3.30659)
$= 2.5$ to $3.5$ | (B1) | | AWFW; even if by interpolation from original data giving likely values of 3 or 3.04
**Alternative:**
$y_{27} = (5.35 \text{ to } 5.36) - 0.076 \times 27$ | M1 | | Clear evidence of correct use of c's equation with $x = 27$
$= 3.28$ to $3.32$ | A1 | 2 | AWFW (3.30659)
## Part (e):
$r(35, 2.5) = -0.21$ to $-0.19$ | B2 | 2 | AWFW; including $-$ve sign $(-0.20000)$
$= 0.1$ to $0.3$ | (B1) | | AWFW; ignore sign
**Alternative:**
$r(35, 2.5) = 2.5 - y_{35}$ | M1 | | Used; allow $y_{35} - 2.5$
$= 2.5 - \{(5.35 \text{ to } 5.36) - 0.076 \times 35\}$ | | |
$= -0.21$ to $-0.19$ | A1 | 2 | AWFW $(-0.20000)$
## Part (f):
Good/reasonable/accurate/correct/etc; Accept more positive qualifying adjectives | B1 | 1 | OE; ignore reasoning; Very good (B1); Not good (B0)
## Part (g)(i):
Extrapolation/outside (observed) range (of $x$) | B1 | 1 | OE
## Part (g)(ii):
$y_{80} = -0.5$ to $-1$ | B1 | | AWFW $(-0.71209)$
Negative value for calorific value is impossible OR More energy needed than is generated | Bdep1 | 2 | OE; dependent on B1; Must be in context; negative value impossible $\Rightarrow$ Bdep0
**Total: 17 marks**
---
5 An experiment was undertaken to collect information on the burning of a specific type of wood as a source of energy. At given fixed levels of the wood's moisture content, $x$ per cent, its corresponding calorific value, $y \mathrm { MWh } /$ tonne, on burning was determined. The results are shown in the table.
\begin{center}
\begin{tabular}{ | c | c | c | c | c | c | c | c | c | c | c | c | c | c | }
\hline
$\boldsymbol { x }$ & 5 & 10 & 15 & 20 & 25 & 30 & 35 & 40 & 45 & 50 & 55 & 60 & 65 \\
\hline
$\boldsymbol { y }$ & 5.2 & 4.7 & 4.3 & 4.0 & 3.2 & 2.8 & 2.5 & 2.2 & 1.8 & 1.5 & 1.3 & 1.0 & 0.6 \\
\hline
\end{tabular}
\end{center}
\begin{enumerate}[label=(\alph*)]
\item Explain why calorific value is the response variable.
\item Calculate the equation of the least squares regression line of $y$ on $x$, giving your answer in the form $y = a + b x$.
\item Interpret, in context, your values for $a$ and $b$.
\item Use your equation to estimate the wood's calorific value when it has a moisture content of 27 per cent.
\item Calculate the value of the residual for the point $( 35,2.5 )$.
\item Given that the values of the 13 residuals lie between - 0.28 and + 0.23 , comment on the likely accuracy of your estimate in part (d).
\item \begin{enumerate}[label=(\roman*)]
\item Give a general reason why your equation should not be used to estimate the wood's calorific value when it has a moisture content of 80 per cent.
\item Give a specific reason, based on the context of this question and with numerical support, why your equation cannot be used to estimate the wood's calorific value when it has a moisture content of 80 per cent.
\end{enumerate}\end{enumerate}
\hfill \mbox{\textit{AQA S1 2012 Q5 [17]}}