OCR MEI S1 2008 January — Question 6 18 marks

Exam BoardOCR MEI
ModuleS1 (Statistics 1)
Year2008
SessionJanuary
Marks18
PaperDownload PDF ↗
Mark schemeDownload PDF ↗
TopicMeasures of Location and Spread
TypeCalculate variance from summary statistics
DifficultyEasy -1.2 This is a routine S1 statistics question testing standard formulas and procedures: calculating mean/SD from summary statistics (direct formula application), checking outliers using a standard rule, applying linear transformations to statistics (textbook formula), and drawing/reading a cumulative frequency graph. All parts require only recall and mechanical application of well-practiced techniques with no problem-solving or novel insight required.
Spec2.02b Histogram: area represents frequency2.02f Measures of average and spread2.02g Calculate mean and standard deviation2.02h Recognize outliers

6 The maximum temperatures \(x\) degrees Celsius recorded during each month of 2005 in Cambridge are given in the table below.
JanFebMarAprMayJunJulAugSepOctNovDec
9.27.110.714.216.621.822.022.621.117.410.17.8
These data are summarised by \(n = 12 , \Sigma x = 180.6 , \Sigma x ^ { 2 } = 3107.56\).
  1. Calculate the mean and standard deviation of the data.
  2. Determine whether there are any outliers.
  3. The formula \(y = 1.8 x + 32\) is used to convert degrees Celsius to degrees Fahrenheit. Find the mean and standard deviation of the 2005 maximum temperatures in degrees Fahrenheit.
  4. In New York, the monthly maximum temperatures are recorded in degrees Fahrenheit. In 2005 the mean was 63.7 and the standard deviation was 16.0 . Briefly compare the maximum monthly temperatures in Cambridge and New York in 2005. The total numbers of hours of sunshine recorded in Cambridge during the month of January for each of the last 48 years are summarised below.
    Hours \(h\)\(70 \leqslant h < 100\)\(100 \leqslant h < 110\)\(110 \leqslant h < 120\)\(120 \leqslant h < 150\)\(150 \leqslant h < 170\)\(170 \leqslant h < 190\)
    Number of years681011103
  5. Draw a cumulative frequency graph for these data.
  6. Use your graph to estimate the 90th percentile.

Q6(i)
AnswerMarks
\(\text{Mean} = \frac{180.6}{12} = 15.05\) or \(15.1\)B1 for mean
\(S_{xx} = 3107.56 - \frac{180.6^2}{12}\) or \(3107.56 - 12(\text{their } 15.05)^2 = (389.53)\)M1 for attempt at \(S_{xx}\); A1 cao
\(s = \sqrt{\frac{389.53}{11}} = 5.95\) or better
NB Accept answers seen without working (from calculator)
TOTAL: 3
Q6(ii)
AnswerMarks
\(\bar{x} + 2s = 15.05 + 2 \times 5.95 = 26.95\)M1 for attempt at either; M1 for both
\(\bar{x} - 2s = 15.05 - 2 \times 5.95 = 3.15\)
So no outliersA1 for limits and conclusion FT their mean and sd
TOTAL: 3
Q6(iii)
AnswerMarks
New mean \(= 1.8 \times 15.05 + 32 = 59.1\)B1FT
New \(s = 1.8 \times 5.95 = 10.7\)M1 A1FT
TOTAL: 3
Q6(iv)
AnswerMarks
New York has a higher mean or 'is on average' higher (oe)E1FT using \(\bar{F}\) (\(\bar{x}\) dep)
TOTAL: 1
Q6(v)
AnswerMarks
New York has greater spread/range/variation or SD (oe)E1FT using \(\sigma\) dep
TOTAL: 1
Q6(vi)
AnswerMarks Guidance
Upper bound70 100
Cumulative frequency0 6
B1 for all correct cumulative frequencies (may be implied from graph). Ignore cf of 0 at this stage
[Cumulative frequency graph with points plotted and joined with smooth curve, showing cumulative frequency (0-50) vs Hours (0-200)]G1 for linear scales (linear from 70 to 190); ignore \(x < 70\); vertical: 0 to 50 but not beyond 100 (no inequality scales); G1 for labels; G1 for points plotted as (UCB, their cf). Ignore (70,0) at this stage. No mid-point or LCB plots.
NB all G marks dep on attempt at cumulative frequencies.G1 for joining all of 'their points' (line or smooth curve) AND now including (70,0)
NB All G marks dep on attempt at cumulative frequencies
Line on graph at cf \(= 43.2\) (soi) or used 90th percentile \(= 166\)M1 for use of 43.2; A1FT but dep on 3rd G mark earned
TOTAL: 5
## Q6(i)

$\text{Mean} = \frac{180.6}{12} = 15.05$ or $15.1$ | B1 for mean | 

$S_{xx} = 3107.56 - \frac{180.6^2}{12}$ or $3107.56 - 12(\text{their } 15.05)^2 = (389.53)$ | M1 for attempt at $S_{xx}$; A1 cao | 

$s = \sqrt{\frac{389.53}{11}} = 5.95$ or better | |

NB Accept answers seen without working (from calculator) | |

| TOTAL: 3 |

## Q6(ii)

$\bar{x} + 2s = 15.05 + 2 \times 5.95 = 26.95$ | M1 for attempt at either; M1 for both |

$\bar{x} - 2s = 15.05 - 2 \times 5.95 = 3.15$ | |

So no outliers | A1 for limits and conclusion FT their mean and sd | 

| TOTAL: 3 |

## Q6(iii)

New mean $= 1.8 \times 15.05 + 32 = 59.1$ | B1FT | 

New $s = 1.8 \times 5.95 = 10.7$ | M1 A1FT | 

| TOTAL: 3 |

## Q6(iv)

New York has a higher mean or 'is on average' higher (oe) | E1FT using $\bar{F}$ ($\bar{x}$ dep) | 

| TOTAL: 1 |

## Q6(v)

New York has greater spread/range/variation or SD (oe) | E1FT using $\sigma$ dep | 

| TOTAL: 1 |

## Q6(vi)

| Upper bound | 70 | 100 | 110 | 120 | 150 | 170 | 190 |
|---|---|---|---|---|---|---|---|
| Cumulative frequency | 0 | 6 | 14 | 24 | 35 | 45 | 48 |

| B1 for all correct cumulative frequencies (may be implied from graph). Ignore cf of 0 at this stage | 

[Cumulative frequency graph with points plotted and joined with smooth curve, showing cumulative frequency (0-50) vs Hours (0-200)] | G1 for linear scales (linear from 70 to 190); ignore $x < 70$; vertical: 0 to 50 but not beyond 100 (no inequality scales); G1 for labels; G1 for points plotted as (UCB, their cf). Ignore (70,0) at this stage. No mid-point or LCB plots. | 

NB all G marks dep on attempt at cumulative frequencies. | G1 for joining all of 'their points' (line or smooth curve) AND now including (70,0) | 

NB All G marks dep on attempt at cumulative frequencies | |

Line on graph at cf $= 43.2$ (soi) or used 90th percentile $= 166$ | M1 for use of 43.2; A1FT but dep on 3rd G mark earned | 

| TOTAL: 5 |

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6 The maximum temperatures $x$ degrees Celsius recorded during each month of 2005 in Cambridge are given in the table below.

\begin{center}
\begin{tabular}{ | c | c | c | c | c | c | c | c | c | c | c | c | }
\hline
Jan & Feb & Mar & Apr & May & Jun & Jul & Aug & Sep & Oct & Nov & Dec \\
\hline
9.2 & 7.1 & 10.7 & 14.2 & 16.6 & 21.8 & 22.0 & 22.6 & 21.1 & 17.4 & 10.1 & 7.8 \\
\hline
\end{tabular}
\end{center}

These data are summarised by $n = 12 , \Sigma x = 180.6 , \Sigma x ^ { 2 } = 3107.56$.\\
(i) Calculate the mean and standard deviation of the data.\\
(ii) Determine whether there are any outliers.\\
(iii) The formula $y = 1.8 x + 32$ is used to convert degrees Celsius to degrees Fahrenheit. Find the mean and standard deviation of the 2005 maximum temperatures in degrees Fahrenheit.\\
(iv) In New York, the monthly maximum temperatures are recorded in degrees Fahrenheit. In 2005 the mean was 63.7 and the standard deviation was 16.0 . Briefly compare the maximum monthly temperatures in Cambridge and New York in 2005.

The total numbers of hours of sunshine recorded in Cambridge during the month of January for each of the last 48 years are summarised below.

\begin{center}
\begin{tabular}{ | l | c | c | c | c | c | c | }
\hline
Hours $h$ & $70 \leqslant h < 100$ & $100 \leqslant h < 110$ & $110 \leqslant h < 120$ & $120 \leqslant h < 150$ & $150 \leqslant h < 170$ & $170 \leqslant h < 190$ \\
\hline
Number of years & 6 & 8 & 10 & 11 & 10 & 3 \\
\hline
\end{tabular}
\end{center}

(v) Draw a cumulative frequency graph for these data.\\
(vi) Use your graph to estimate the 90th percentile.

\hfill \mbox{\textit{OCR MEI S1 2008 Q6 [18]}}