| Exam Board | OCR |
|---|---|
| Module | PURE |
| Marks | 8 |
| Paper | Download PDF ↗ |
| Topic | Bivariate data |
| Type | Interpret census or real-world data |
| Difficulty | Easy -1.8 This is a data interpretation question requiring only careful reading comprehension and basic understanding of percentages. Part (a) asks students to notice that 'largest decreases' means ordered by the driving column, not necessarily the 15 largest in absolute terms (could be ties, or the selection criterion isn't fully specified). Part (b) appears incomplete but likely asks for simple identification from the table. No calculations or statistical techniques are required—just careful reading of context and data. |
| Spec | 2.02a Interpret single variable data: tables and diagrams2.02i Select/critique data presentation |
| Local Authority | Work mainly at or from home | Underground, metro, light rail, tram | Train | Bus, minibus or coach | Driving a car or van | Passenger in a car or van | Bicycle | On foot |
| Brighton and Hove | 3.2 | 0.1 | 1.5 | 0.8 | -8.2 | -1.5 | 2.1 | 2.3 |
| Cambridge | 2.2 | 0.0 | 1.6 | 1.2 | -7.4 | -1.0 | 3.1 | 0.6 |
| Elmbridge | 2.9 | 0.4 | 4.1 | 0.2 | -6.6 | -0.7 | 0.3 | -0.3 |
| Oxford | 2.0 | 0.0 | 0.6 | -0.4 | -5.2 | -1.1 | 2.2 | 2.1 |
| Epsom and Ewell | 1.6 | 0.4 | 3.9 | 1.1 | -5.2 | -0.9 | 0.0 | -0.6 |
| Watford | 0.7 | 2.0 | 3.1 | 0.4 | -4.5 | -1.2 | 0.0 | -0.1 |
| Tandridge | 3.3 | 0.2 | 4.0 | -0.1 | -4.5 | -1.1 | 0.0 | -1.3 |
| Mole Valley | 3.3 | 0.1 | 1.9 | 0.3 | -4.4 | -0.7 | 0.2 | -0.3 |
| St Albans | 2.3 | 0.3 | 3.4 | -0.3 | -4.3 | -1.2 | 0.3 | -0.2 |
| Chiltern | 2.9 | 1.4 | 1.4 | 0.1 | -4.2 | -0.6 | -0.2 | -0.8 |
| Exeter | 0.7 | 0.0 | 1.0 | -0.6 | -4.2 | -1.5 | 1.7 | 3.4 |
| Woking | 2.1 | 0.1 | 3.7 | 0.0 | -4.2 | -1.3 | -0.1 | 0.0 |
| Reigate and Banstead | 1.8 | 0.1 | 3.2 | 0.6 | -4.1 | -1.0 | 0.1 | -0.2 |
| Waverley | 4.3 | 0.1 | 2.5 | -0.5 | -3.9 | -0.9 | -0.3 | -0.9 |
| Guildford | 2.7 | 0.1 | 2.4 | 0.2 | -3.6 | -1.2 | 0.0 | -0.3 |
| Answer | Marks | Guidance |
|---|---|---|
| The table does not include London LAs, so one of them might have had a greater increase. These areas may not have as large decrease as areas such as London | B1 (2.2b) | NOT: "Not include London" plus incorrect e.g. "small sample"; Not include London and other cities; There could be other LAs with bigger decreases in other years |
| Answer | Marks | Guidance |
|---|---|---|
| Brighton and Hove, Oxford, Cambridge, Exeter. | B1* (1.1) | All four required |
| E.g. they have relatively high (positive) values in the Bicycle and Walking columns | B1dep (2.2a) | or e.g. they have the largest increases (or changes) in percentage cycling & walking or they have largest total increase for cycling and walking. Must mention both cycling and walking |
| Answer | Marks |
|---|---|
| No, e.g. Data given is proportions, so there may be LAs with large populations where the absolute change is larger but the proportion of total population is smaller. No, e.g. data does not show population sizes | A1 (2.2b) |
| Answer | Marks | Guidance |
|---|---|---|
| Work mainly at or from home | B1 (2.2b) | Subtract B1 for each extra category quoted |
| Train | B1 (2.2b) | NOT: These two categories are positive for all LAs |
| E.g. These two categories have entries above 1.0 except in 3 cases. These two categories' entries all above 0.6. No other method of travel has more than 3 entries greater than 2.0. Both are all positive and have largest home (4.3) and largest train (4.1). Both are all over 0.5. Smallest home 0.7, smallest train 0.6. Average increases: Home 2.4, Train 2.55 (must be correct). Total increases: Home 36, Train 38.3 (correct) | B1 (2.4) | This B1 can only be awarded if B1B1 already scored. Good explanation of why these two are significantly different from the others. Must quote at least two figures from table, from any two categories, or two correct totals or averages |
| Answer | Marks | Guidance |
|---|---|---|
| Not the case. The "driving" figures increase, but the "home" figures have no pattern. | B1 (2.3) | Not enough to quote individual LAs. Not weak correlation |
# Question 9(a):
The table does not include London LAs, so one of them might have had a greater increase. These areas may not have as large decrease as areas such as London | B1 (2.2b) | NOT: "Not include London" plus incorrect e.g. "small sample"; Not include London and other cities; There could be other LAs with bigger decreases in other years
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# Question 9(b):
Brighton and Hove, Oxford, Cambridge, Exeter. | B1* (1.1) | All four required
E.g. they have relatively high (positive) values in the Bicycle and Walking columns | B1dep (2.2a) | or e.g. they have the largest increases (or changes) in percentage cycling & walking or they have largest total increase for cycling and walking. Must mention both cycling and walking
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# Question 9(c):
No, e.g. Data given is proportions, so there may be LAs with large populations where the absolute change is larger but the proportion of total population is smaller. No, e.g. data does not show population sizes | A1 (2.2b) |
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# Question 9(d):
Work mainly at or from home | B1 (2.2b) | Subtract B1 for each extra category quoted
Train | B1 (2.2b) | NOT: These two categories are positive for all LAs
E.g. These two categories have entries above 1.0 except in 3 cases. These two categories' entries all above 0.6. No other method of travel has more than 3 entries greater than 2.0. Both are all positive and have largest home (4.3) and largest train (4.1). Both are all over 0.5. Smallest home 0.7, smallest train 0.6. Average increases: Home 2.4, Train 2.55 (must be correct). Total increases: Home 36, Train 38.3 (correct) | B1 (2.4) | This B1 can only be awarded if B1B1 already scored. Good explanation of why these two are significantly different from the others. Must quote at least two figures from table, from any two categories, or two correct totals or averages
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# Question 9(e):
Not the case. The "driving" figures increase, but the "home" figures have no pattern. | B1 (2.3) | Not enough to quote individual LAs. Not weak correlation
---9 A researcher is studying changes in behaviour in travelling to work by people who live outside London, between 2001 and 2011.
He chooses the 15 Local Authorities (LAs) outside London with the largest decreases in the percentage of people driving to work, and arranges these in descending order.
The table shows the changes in percentages from 2001 to 2011 in various travel categories, for these Local Authorities.
\begin{center}
\begin{tabular}{|l|l|l|l|l|l|l|l|l|}
\hline
Local Authority & Work mainly at or from home & Underground, metro, light rail, tram & Train & Bus, minibus or coach & Driving a car or van & Passenger in a car or van & Bicycle & On foot \\
\hline
Brighton and Hove & 3.2 & 0.1 & 1.5 & 0.8 & -8.2 & -1.5 & 2.1 & 2.3 \\
\hline
Cambridge & 2.2 & 0.0 & 1.6 & 1.2 & -7.4 & -1.0 & 3.1 & 0.6 \\
\hline
Elmbridge & 2.9 & 0.4 & 4.1 & 0.2 & -6.6 & -0.7 & 0.3 & -0.3 \\
\hline
Oxford & 2.0 & 0.0 & 0.6 & -0.4 & -5.2 & -1.1 & 2.2 & 2.1 \\
\hline
Epsom and Ewell & 1.6 & 0.4 & 3.9 & 1.1 & -5.2 & -0.9 & 0.0 & -0.6 \\
\hline
Watford & 0.7 & 2.0 & 3.1 & 0.4 & -4.5 & -1.2 & 0.0 & -0.1 \\
\hline
Tandridge & 3.3 & 0.2 & 4.0 & -0.1 & -4.5 & -1.1 & 0.0 & -1.3 \\
\hline
Mole Valley & 3.3 & 0.1 & 1.9 & 0.3 & -4.4 & -0.7 & 0.2 & -0.3 \\
\hline
St Albans & 2.3 & 0.3 & 3.4 & -0.3 & -4.3 & -1.2 & 0.3 & -0.2 \\
\hline
Chiltern & 2.9 & 1.4 & 1.4 & 0.1 & -4.2 & -0.6 & -0.2 & -0.8 \\
\hline
Exeter & 0.7 & 0.0 & 1.0 & -0.6 & -4.2 & -1.5 & 1.7 & 3.4 \\
\hline
Woking & 2.1 & 0.1 & 3.7 & 0.0 & -4.2 & -1.3 & -0.1 & 0.0 \\
\hline
Reigate and Banstead & 1.8 & 0.1 & 3.2 & 0.6 & -4.1 & -1.0 & 0.1 & -0.2 \\
\hline
Waverley & 4.3 & 0.1 & 2.5 & -0.5 & -3.9 & -0.9 & -0.3 & -0.9 \\
\hline
Guildford & 2.7 & 0.1 & 2.4 & 0.2 & -3.6 & -1.2 & 0.0 & -0.3 \\
\hline
\end{tabular}
\end{center}
\begin{enumerate}[label=(\alph*)]
\item Explain why these LAs are not necessarily the 15 LAs with the largest decreases in the percentage of people driving to work.
\item The researcher wants to talk to those LAs outside London which have been most successful in encouraging people to change to cycling or walking to work.\\
Suggest four LAs that he should talk to and why.
\item The researcher claims that Waverley is the LA outside London which has had the largest increase in the number of people working mainly at or from home.\\
Does the data support his claim? Explain your answer.
\item Which two categories have replaced driving to work for the highest percentages of workers in these LAs? Support your answer with evidence from the table.
\item The researcher suggested that there would be strong correlation between the decrease in the percentage driving to work and the increase in percentage working mainly at or from home. Without calculation, use data from the table to comment briefly on this suggestion.
\end{enumerate}
\hfill \mbox{\textit{OCR PURE Q9 [8]}}