Coastal Enquiry Skills

Why data presentation matters

Once you've stood on a beach measuring pebbles and waves, you end up with a big messy table of numbers. On its own, that table is almost useless — nobody can look at 50 rows of digits and instantly "see" a pattern. Data presentation turns raw numbers into a visual story that makes patterns, trends, and anomalies jump out at a glance.

The trick the exam wants you to understand isn't just "how do I draw a graph" — it's which graph fits which type of data, because each graph type is built to answer a different kind of question.

Primary data — the graphs you'll actually be tested on

Primary data is data you collected yourself out in the field (pebble sizes, wave counts, beach gradients). Here are the three main graph types Edexcel expects you to know, and — more importantly — why each one is the right tool for its job:

Worked Example — completing a bar graph and spotting the anomaly

Here's the key distinction the exam wants you to be crystal clear on: primary data is data you collect yourself in the field (measuring pebbles, counting waves), while secondary data is data that already existed before your enquiry, collected by someone else, that you use to add context.

Why bother with secondary data at all if you already have your own measurements? Because primary data on its own is a snapshot — it tells you what the beach looked like on the one day you visited, but it can't tell you about longer-term change, weather conditions on the day, or the wider geological setting. Secondary data fills in those gaps.

Useful secondary data sources for a coastal enquiry

• Met Office weather/rainfall data — tells you if unusual weather (a storm, high winds) affected your results on the day you collected data.
• Old photographs of the coastal site — lets you compare "then vs. now" to see how the coastline has physically changed.
• Newspaper articles / websites about the coastal area — can reveal recent events like storm damage, erosion incidents, or coastal management schemes.
• Ordnance Survey (OS) maps — used to identify exactly where your sample sites are and plan a sensible route/spacing between them.
• Geology maps — show the rock type of the coastal cliffs, which helps explain why erosion rates differ between sites.
• Aerial photographs — show changes in the beach profile from above, useful for spotting bigger-picture shifts in shape.
• Shoreline Management Plans (SMPs) from local authorities, the Environment Agency, or government — outline long-term coastal management strategy for the area.

Quantitative analysis — working with numbers

Once your data is collected and presented, it isn't finished — it needs to be analysed. Data like beach slope and pebble size is quantitative (numerical), so the exam expects you to process it using basic statistics, mainly the mean and the median.

Qualitative analysis — working with photos & sketches

Not everything you collect is a number. Photographs and field sketches are analysed qualitatively — meaning you describe and interpret what they show rather than calculate anything from them. In a coastal enquiry, photos are typically used to analyse two things:

• Landforms and their formation — e.g. a photo of a headland showing wave-cut notches, or a spit showing longshore drift deposition.
• Data collection techniques — e.g. a photo showing exactly how a student measured beach gradient with a clinometer, used as evidence the method was followed correctly.

Conclusion — what did you actually find out?

Once your data has been analysed, you write a conclusion. This is where you go back to your original hypothesis (the prediction you were testing) and state, using your actual results as evidence, whether it was proved or disproved. A strong conclusion also identifies and explains any anomalies you found rather than just ignoring them — common causes include:

• A recent rockfall making a sample size unusually large.
• A sample being taken from a protected area, or near a groyne, where erosion is reduced.
• Incorrect recording or human error when reading equipment.

Evaluation — was the whole enquiry actually any good?

This is the final, and often hardest, stage: stepping back and honestly judging how successful the investigation was, and what you'd change if you did it again. Don't confuse this with the conclusion — the conclusion is about your results; the evaluation is about your methods and process.

A strong evaluation covers three areas:

1. Issues with the enquiry design — Were the sampling methods appropriate? Were more sample sites needed? Would a different sampling technique or different equipment have worked better? How did any of this affect your ability to answer the enquiry question?
2. Issues with analysis methods — Were the methods you used (mean, median, best-fit lines) actually appropriate for your data? Were there alternative methods that might have worked better?
3. Issues with equipment — Was any equipment faulty? Were there problems reading measurements accurately? How did this affect your results?