OCR MEI S2 2016 June — Question 3 18 marks

Exam BoardOCR MEI
ModuleS2 (Statistics 2)
Year2016
SessionJune
Marks18
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicNormal Distribution
TypeProbability calculation plus find unknown boundary
DifficultyModerate -0.3 This is a straightforward application of normal distribution techniques with standard procedures: z-score calculations, percentage point lookups, and solving simultaneous equations with inverse normal values. All parts follow textbook methods with no novel problem-solving required, though part (iv) requires slightly more algebraic manipulation than typical. Slightly easier than average due to routine nature.
Spec2.04e Normal distribution: as model N(mu, sigma^2)2.04f Find normal probabilities: Z transformation

3 Many types of computer have cooling fans. The random variable \(X\) represents the lifetime in hours of a particular model of cooling fan. \(X\) is Normally distributed with mean 50600 and standard deviation 3400.
  1. Find \(\mathrm { P } ( 50000 < X < 55000 )\).
  2. The manufacturers claim that at least \(95 \%\) of these fans last longer than 45000 hours. Is this claim valid?
  3. Find the value of \(h\) for which \(99.9 \%\) of these fans last \(h\) hours or more.
  4. The random variable \(Y\) represents the lifetime in hours of a different model of cooling fan. \(Y\) is Normally distributed with mean \(\mu\) and standard deviation \(\sigma\). It is known that \(\mathrm { P } ( Y < 60000 ) = 0.6\) and \(\mathrm { P } ( Y > 50000 ) = 0.9\). Find the values of \(\mu\) and \(\sigma\).
  5. Sketch the distributions of lifetimes for both types of cooling fan on a single diagram.

Question 3:
Part (i)
AnswerMarks Guidance
AnswerMarks Guidance
\(P(50000 < X < 55000) = P\!\left(\dfrac{50000 - 50600}{3400} < Z < \dfrac{55000 - 50600}{3400}\right)\)M1 For standardising both. SOI. Penalise erroneous continuity corrections and wrong sd. Condone numerator(s) reversed.
\(= P(-0.176 < Z < 1.294) = \Phi(1.294) - (1 - \Phi(0.176)) = 0.9022 - 1 + 0.5699\)M1 For correct structure \(\Phi(\text{positive } z) - \Phi(\text{negative } z)\)
\(= 0.4721\)A1 CAO including use of difference tables (Answer from calculator 0.4722 and from tables interpolated 0.4723)
[3]
Question 3(ii):
AnswerMarks Guidance
AnswerMarks Guidance
\(P(X > 45000) = P\left(Z \geq \frac{750-751.4}{2.5}\right)\left(Z > \frac{45000-50600}{3400}\right) = P(Z > -1.647)\)B1* For \(-1.647\) or \(-\Phi^{-1}(0.95) = -1.645\) or \(1.647\) seen with \(P(X < 56200)\) or numerator reversed
\(= \Phi(1.647) = 0.9502\)B1* For \(0.9502\) or \(45007\) or \(0.0498\), or B1 for \(-1.645\) if B1 for \(-1.647\) already awarded
\(0.9502 > 95\%\) so agree with claimdepE1* For comparison seen e.g. \(-1.647 < -1.645\) or \(0.0498 < 0.05\) or \(1.647 > 1.645\) or \(95\%\) last longer than 45007 hours, and correct conclusion. Dependent on B1, B1 awarded
Question 3(iii):
AnswerMarks Guidance
AnswerMarks Guidance
From tables \(\Phi^{-1}(0.999) = 3.09\)B1 \(\pm 3.09\) seen
\(\frac{h - 50600}{3400} = -3.09\)M1 For equation with their negative z-value
\(k = 50600 - (3.09 \times 3400) = 40100\)A1 [3] CAO Allow 40094, 40090
Question 3(iv):
AnswerMarks Guidance
AnswerMarks Guidance
\(P(Y < 60000) = 0.6 \Rightarrow P\left(Z < \frac{60000-\mu}{\sigma}\right) = 0.6\)B1 For \(\pm 0.2533\) or \(\pm 1.282\) seen
\(\Rightarrow \frac{60000-\mu}{\sigma} = \Phi^{-1}(0.6) = 0.2533\)M1 For an equation in \(\mu\), \(\sigma\), \(z\) and \(y\) formed. NB using \(z = \pm 0.2533\) with \(y = 60000\) or \(\pm 1.282\) with \(y = 50000\)
\(\Rightarrow 60000 = \mu + 0.2533\sigma\)
\(P(Y > 50000) = 0.9 \Rightarrow P\left(Z > \frac{50000-\mu}{\sigma}\right) = 0.9\)
\(\Rightarrow \frac{50000-\mu}{\sigma} = \Phi^{-1}(0.1) = -1.282\)A1 For two correct equations seen
\(\Rightarrow 50000 = \mu - 1.282\sigma\)
\(1.5353\sigma = 10000\), \(\sigma = 6513\)A1 CAO Allow 6510, 6515
\(\Rightarrow \mu = 50000 + (1.282 \times 6513) = 58350\)A1 [5] CAO Allow 58400
Question 3(v):
AnswerMarks Guidance
AnswerMarks Guidance
Two Normal curve shapes shownG1 For two Normal shapes including attempt at asymptotic behaviour with horizontal axis at each of the four ends. Penalise clear asymmetry
Means shown explicitly or by scale on a single diagramG1 If shown explicitly, positions must be consistent with horizontal scale if present. FT part (iv)
Greater width (variance) for Different modelG1 FT part (iv)
Lower max height for Different modelG1 [4] FT part (iv). If not labelled assume the larger mean represents Different model
# Question 3:

## Part (i)
| Answer | Marks | Guidance |
|--------|-------|----------|
| $P(50000 < X < 55000) = P\!\left(\dfrac{50000 - 50600}{3400} < Z < \dfrac{55000 - 50600}{3400}\right)$ | M1 | For standardising both. SOI. Penalise erroneous continuity corrections and wrong sd. Condone numerator(s) reversed. |
| $= P(-0.176 < Z < 1.294) = \Phi(1.294) - (1 - \Phi(0.176)) = 0.9022 - 1 + 0.5699$ | M1 | For correct structure $\Phi(\text{positive } z) - \Phi(\text{negative } z)$ |
| $= 0.4721$ | A1 | CAO including use of difference tables (Answer from calculator 0.4722 and from tables interpolated 0.4723) |
| **[3]** | | |

## Question 3(ii):

| Answer | Marks | Guidance |
|--------|-------|----------|
| $P(X > 45000) = P\left(Z \geq \frac{750-751.4}{2.5}\right)\left(Z > \frac{45000-50600}{3400}\right) = P(Z > -1.647)$ | B1* | For $-1.647$ or $-\Phi^{-1}(0.95) = -1.645$ or $1.647$ seen with $P(X < 56200)$ or numerator reversed |
| $= \Phi(1.647) = 0.9502$ | B1* | For $0.9502$ or $45007$ or $0.0498$, or B1 for $-1.645$ if B1 for $-1.647$ already awarded |
| $0.9502 > 95\%$ so agree with claim | depE1* | **For comparison seen** e.g. $-1.647 < -1.645$ or $0.0498 < 0.05$ or $1.647 > 1.645$ or $95\%$ last longer than 45007 hours, **and correct conclusion**. Dependent on B1, B1 awarded |

## Question 3(iii):

| Answer | Marks | Guidance |
|--------|-------|----------|
| From tables $\Phi^{-1}(0.999) = 3.09$ | B1 | $\pm 3.09$ seen |
| $\frac{h - 50600}{3400} = -3.09$ | M1 | For equation with their negative z-value |
| $k = 50600 - (3.09 \times 3400) = 40100$ | A1 [3] | CAO Allow 40094, 40090 |

## Question 3(iv):

| Answer | Marks | Guidance |
|--------|-------|----------|
| $P(Y < 60000) = 0.6 \Rightarrow P\left(Z < \frac{60000-\mu}{\sigma}\right) = 0.6$ | B1 | For $\pm 0.2533$ or $\pm 1.282$ seen |
| $\Rightarrow \frac{60000-\mu}{\sigma} = \Phi^{-1}(0.6) = 0.2533$ | M1 | For an equation in $\mu$, $\sigma$, $z$ and $y$ formed. NB using $z = \pm 0.2533$ with $y = 60000$ or $\pm 1.282$ with $y = 50000$ |
| $\Rightarrow 60000 = \mu + 0.2533\sigma$ | | |
| $P(Y > 50000) = 0.9 \Rightarrow P\left(Z > \frac{50000-\mu}{\sigma}\right) = 0.9$ | | |
| $\Rightarrow \frac{50000-\mu}{\sigma} = \Phi^{-1}(0.1) = -1.282$ | A1 | For two correct equations seen |
| $\Rightarrow 50000 = \mu - 1.282\sigma$ | | |
| $1.5353\sigma = 10000$, $\sigma = 6513$ | A1 | CAO Allow 6510, 6515 |
| $\Rightarrow \mu = 50000 + (1.282 \times 6513) = 58350$ | A1 [5] | CAO Allow 58400 |

## Question 3(v):

| Answer | Marks | Guidance |
|--------|-------|----------|
| Two Normal curve shapes shown | G1 | For two Normal shapes including attempt at asymptotic behaviour with horizontal axis at each of the four ends. Penalise clear asymmetry |
| Means shown explicitly or by scale **on a single diagram** | G1 | If shown explicitly, positions must be consistent with horizontal scale if present. FT part (iv) |
| Greater width (variance) for Different model | G1 | FT part (iv) |
| Lower max height for Different model | G1 [4] | FT part (iv). If not labelled assume the larger mean represents Different model |
3 Many types of computer have cooling fans. The random variable $X$ represents the lifetime in hours of a particular model of cooling fan. $X$ is Normally distributed with mean 50600 and standard deviation 3400.\\
(i) Find $\mathrm { P } ( 50000 < X < 55000 )$.\\
(ii) The manufacturers claim that at least $95 \%$ of these fans last longer than 45000 hours. Is this claim valid?\\
(iii) Find the value of $h$ for which $99.9 \%$ of these fans last $h$ hours or more.\\
(iv) The random variable $Y$ represents the lifetime in hours of a different model of cooling fan. $Y$ is Normally distributed with mean $\mu$ and standard deviation $\sigma$. It is known that $\mathrm { P } ( Y < 60000 ) = 0.6$ and $\mathrm { P } ( Y > 50000 ) = 0.9$. Find the values of $\mu$ and $\sigma$.\\
(v) Sketch the distributions of lifetimes for both types of cooling fan on a single diagram.

\hfill \mbox{\textit{OCR MEI S2 2016 Q3 [18]}}