Analysis of Results

Question 1

Method

Answer 1

• The technique we used to analyse our results was carrying out a Spearman’s Rank Correlation Co-efficient
• The reason why we did this was to establish whether there was a statistical correlation (relationship) between discharge and sediment size
• This would then enable us to prove or disprove our hypotheses and see how well Wycoller Beck fits the Bradshaw Model

How to work out a Spearman’s Rank Correlation Co-efficient:

1. Firslty, we formulated a Test and Null Hypothesis - Test Hypothesis: As discharge (m³s) increases, sediment size (mm) will decrease - Null Hypothesis: There will be no correlation between discharge and sediment size
2. Then we drew a scatter graph with the 2 variables of discharge and sediment size
3. After this, we drew an appropriate table and worked out the ranks of the values and the consequent d² value
4. Following this, we applied the numbers into the Spearman’s Rank Correlation Co-efficient equation to get the r_s value

Question 2

Analysis of results

Answer 2

Overall, from our fieldwork investigation, we proved both our hypotheses, which in turn justified the Bradshaw Model which formed the basis of our enquiry.

The first line graph were drew (X-axis being “Distance (d/s) ((m))”, Y-axis being “Discharge (cumecs)”) depicted a strong positive correlation that as the distance from the river source increases the discharge of the river elevates too e.g. the discharge was 0.019 m3/s at the source (site 1) where as, the discharge was 0.444 m3/s 1800 metres away from the source (site 19). So, we could accept our first hypothesis - that River Discharge (m³s) will increases with distance downstream.

{On the graph, the sharp increase that can be seen between site 16 and site 19 was due to a river confluence, and the anomaly (the decrease from site 19 to site 20) was due to human influences e.g. ford near the village.}

We could also accept our second and most important hypothesis (that as discharge (m³s) increases sediment size (mm) will decrease as we calculated a Spearman’s Rank Correlation Co-efficient:

In terms of numerical difference, our r_s value (-0.906) was very close to -1 (perfect negative correlation), meaning that a negative correlation was very likely.

To further measure the strength of our rs value (-0.906) we applied it into a degrees of freedom graph.

Our data plot was above the 0.1% curved line for significance level.

So we were 99.9% confident that our results occured by geographical science rather than by chance so we could accept our test hypothesis; that as discharge (m³s) increases sediment size (mm) will decrease.

This means that the sediment size and river velocity measurements we collected at Wycoller Beck justify the Bradshaw Model as there was a statistical signifcance- that as distance downstream increases the discharge will increase but sediment size will decrease.