A geography department investigated whether house prices rise with distance from an urban railway station. Fig. 1 is a scatter graph made from estate-agent ...
Question 1 Report
A geography department investigated whether house prices rise with distance from an urban railway station. Fig. 1 is a scatter graph made from estate-agent listings collected during one week. Each point represents one three-bedroom house. The horizontal axis shows distance from the station in kilometres and the vertical axis shows asking price in thousands of pounds. A line of best fit has been added. The study is useful for exploring a possible relationship, but the researchers know that house condition, school catchment area, size of garden and local environmental quality may also affect price. They need to interpret the figure rather than assume that correlation proves a cause.
(a) Identify the type of relationship shown by the line of best fit. [2]
(b) Identify the estimated asking price of a house 4 km from the station, using the line of best fit. [2]
(c) Identify the approximate decrease in price predicted between 1 km and 5 km from the station. [3]
(d) Identify one anomalous point on the graph and identify why it may need further investigation. [3]
(e) Identify three factors, other than distance from the station, that could influence asking price. [3]
(f) Identify two ways the researchers could improve the representativeness of their data collection. [4]
(g) Identify one justified conclusion and one limitation of using this figure to advise a house buyer. [3]
Answer Details
(a) The line of best fit shows a negative correlation: as distance from the station increases, asking price tends to decrease. [2]
(b) At 4 km, read from the line of best fit to the price axis. The estimate is approximately £245 000 to £250 000. This is an estimate because it comes from a trend line rather than a plotted house. [2]
(c) From the trend line, the predicted price is approximately £350 000 at 1 km and £210 000 at 5 km:
\[£350\,000-£210\,000=£140\,000\]
The predicted decrease is about £140 000. [3]
(d) An anomalous point is approximately 2.7 km and £330 000. It lies well above the overall trend, so it should be investigated for a different house size, condition or location, or for a recording error. [3]
(e) Other factors affecting price include:
- house condition;
- floor area or number of rooms;
- garden size.
School catchment, crime level and local environmental quality are also valid. [3]
(f) Representativeness could be improved by:
- collecting more listings;
- sampling over a longer period;
- using several estate agents or websites;
- including different neighbourhoods while controlling for similar property type.
Random or systematic selection is also valid. [4]
(g) In this sample, houses nearer the station generally have higher asking prices. However, correlation does not prove that distance from the station causes price: other factors may be responsible. The evidence is also limited to one week, one house type and asking prices rather than sale prices. [3]
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