Analysing Results

Data Presentation

Presenting fieldwork data clearly is essential for effective analysis. Use a variety of formats such as tables, graphs, and maps to display your data. Each format serves a different purpose:

• Tables organise raw data systematically, making it easier to spot values and compare figures.
• Graphs (e.g., bar charts, line graphs) help visualise trends and patterns over time or between locations.
• Maps show spatial distribution and location-based data, useful for physical and human geography.

Always include clear labels, units, and a descriptive title for each presentation. For example, if measuring river velocity, label the axes as Distance downstream $\left(\mathrm{m}\right)$ and Velocity $\left(5.6\,\mathrm{m\,s^{-1}}\right)$. This ensures anyone reading your data understands what is being shown.

Data Analysis Techniques

Once data is presented, the next step is to analyse it to identify patterns, trends, and relationships. Key techniques include:

• Identifying patterns and trends: Look for increases, decreases, clusters, or cycles in your data. For example, river velocity might increase downstream due to gradient changes.
• Calculating averages: Use mean, median, and mode to summarise data sets and reduce the effect of anomalies.
• Comparing results with hypotheses: Check if your data supports or contradicts your initial predictions or expectations.

For example, if you hypothesised that foot traffic is higher in the town centre than in residential areas, compare your pedestrian counts to see if this is true.

The mean is calculated by adding all values and dividing by the number of values. The median is the middle value when data is ordered, and the mode is the most frequently occurring value.

For instance, if you recorded the following river widths (in metres): 4, 5, 6, 6, 7, the mean width is:

$\frac{4 + 5 + 6 + 6 + 7}{5} = \frac{28}{5} = 5.6\,\mathrm{m}$

Additionally, the mode of these values is 6, as it appears most frequently.

Interpreting Results

Interpreting results means explaining why the patterns and trends you observed have occurred. This involves:

• Explaining causes: Use geographical knowledge to link your findings to natural processes or human activities. For example, increased erosion downstream might be due to steeper slopes or higher water volume.
• Linking to theory: Connect your results to geographical theories or models, such as the Bradshaw Model for river changes downstream.
• Considering anomalies: Identify any unexpected results or outliers and suggest reasons why they might have occurred, such as measurement errors or unusual weather conditions.

For example, if a pedestrian count is unusually low in a busy area, this could be due to bad weather on the day of data collection.

When interpreting, always refer back to your data and avoid unsupported assumptions.

Evaluating Results

Evaluating your results involves assessing how reliable and valid your data and methods were, and suggesting improvements. Key points include:

• Reliability: Consider if your data collection was consistent and repeatable. Were measurements taken carefully? Did you use the same method each time?
• Validity: Assess whether your data truly measures what you intended. For example, does your method accurately capture foot traffic or river velocity?
• Limitations: Identify any factors that may have affected your results, such as small sample size, poor weather, or equipment faults.
• Improvements: Suggest how to improve future studies, such as increasing sample size, using more precise instruments, or collecting data at different times.

For example, if you only collected data on one day, your results might not represent typical conditions. Collecting data across several days would improve reliability.