What this lesson teaches
I can organise fieldwork data and analyse its patterns with counts, averages and comparisons.
Syllabus K329, Topic 1.3, Key Question 3. How to process and analyse data?
I can present fieldwork findings with clear maps, graphs, sketches and text.
Syllabus K329, Topic 1.3, Key Question 4. How to present findings?
I can read maps, graphs, photographs and texts, and separate what they show from what they suggest.
Syllabus K329, Topic 1.3, Key Question 4 (part). How to present findings?
Make a guess
A scatter graph shows people who live farther from a park tend to visit it less. Does this prove distance causes fewer visits?
- Yes, because the points slope downwards.
- No, because scatter graphs cannot show any link.
- Yes, if a best-fit line touches every point.
- No. It shows a link, not the cause.
Show the answer
No. It shows a link, not the cause.
A correlation shows two measurements change together. Transport, health or free time could also matter, so other evidence is needed.
A scatter graph shows whether two measurements tend to change together, but it cannot prove why.
Each point on a scatter graph shows two measurements for the same person. In this practice survey, they are distance from the park in metres and visits in the past seven days. The pairs are (100, 6), (200, 5), (300, 4), (400, 5), (500, 2) and (600, 1).
Put distance on the horizontal axis and visits on the vertical axis. Plot each pair as a dot. Do not join the dots, because they are different people.
The points slope down from left to right. This is a negative correlation: more distance tends to go with fewer visits. The person at 400 m is an exception, with 5 visits. A positive correlation slopes upwards. No correlation shows no clear direction.
A best-fit line shows the overall trend, with points on both sides. It does not need to touch every point or pass through zero. The pattern does not prove distance causes fewer visits. Transport, health or free time may matter too, and interviews can test these ideas. Predictions beyond the measured distances are uncertain.
- Negative correlation
- One goes up as the other goes down.
- Best-fit line
- Shows the overall trend; need not touch every point.
- Correlation is not cause
- Other factors may explain the pattern.
Step by step
Keep pairs together
Distance and visits must belong to the same person.
Describe the link
Positive, negative or none, plus exceptions.
Test the cause
Look for other factors before claiming a cause.
Worked example: What an interview could add
The person 400 m away might use a shady, direct path. Someone 300 m away might face a busy road. An interview could test this idea, but it stays a hypothesis until the routes are checked.
Watch out for this
A best-fit line should join every point.
It shows the overall trend. Joining every point suggests an order that separate people do not have.
Check your understanding
What conclusion does the practice scatter graph support?
- More distance generally goes with fewer visits.
- Distance is proven to cause the fall in visits.
- The point at 400 m must be deleted, because it does not fit the trend.
Show the answer
More distance generally goes with fewer visits.
Yes. It describes the trend without claiming a cause.
Check your understanding
A scatter graph shows park visits fall as distance from the park rises. What can you conclude?
- Distance causes the fall in visits, because the points form a clear line.
- There is a positive correlation, because both values change together.
- A negative correlation, which does not prove distance causes it.
Show the answer
A negative correlation, which does not prove distance causes it.
Other factors, like free time or transport, may matter.