The data to be collected was quantitative data; this is basically just numerical data involving numbers. I collected my data using a piece of equipment called a quadrat. This is a 1-sq. metre frame consisting of 4 1-metre rulers attached together in a square shape. I would place the quadrat on a part of the beach and collect the data. To determine which parts of the beach I placed the quadrat on, I chose to use sampling. This would refrain me from biasing my results and leaving them inaccurate and incorrect. There were many different types of sampling to chose from, I had to decide which one would be the most relevant to my investigation and collection of data.

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There was random sampling, which is where I would just randomly throw the quadrat on to a part of the beach. This method I discarded because I feared that I might be biased which direction I threw the quadrat. Another method was stratified sampling. These involved measuring a whole area and then collect fractions of data from every part of the area. This would probably be the most accurate way to collect my data but it is extremely time consuming for a whole area of rocky beach. This method was discarded.

Out of the methods of collecting data that were available I chose systematic sampling. This is when you form a relevant pattern of collecting the data, like placing the quadrat every 10 metres until you reach the sea and collecting the data per quadrat. This sampling method most suited my task because it was not very time consuming and I could not be biased to where I would place the quadrat, I would also hopefully get results from quite a lot of different sources. Methods Here is a simple diagram of the beach we visited; it shows my systematic sampling method and how I proceeded from the road to the seashore. Please note that this diagram is not to scale: –

By using systematic sampling I decided to place the quadrat every 10 metres in a straight line from the road to the sea. To accurately measure 10 metres each time I had a piece of string exactly 10 metres long that I had prepared previously. A partner and me stretched it from the centre of the quadrat to another area of beach. Once the quadrat was placed in its position, I had to collect up the data. I counted the number of limpets and periwinkles and charted them in my results table on a clipboard.

I also used a steel ruler to measure the limpets’ heights because the steel rulers are very accurately made and were durable for their use that day. To determine the percentage of seaweed in each quadrat we laid the seaweed out from one corner of the quadrat and approximated the percentage area of the quadrat that it took up, then we returned it to its natural positioning, so as not to harm the environment in any way.

My aim by collecting this data is to help to prove or disprove my hypotheses, or to give me a deeper understanding of the marine life that I am analysing. I will plot the heights of limpets by the distance from the sea on a graph and hopefully it will show positive correlation (heights increase with distance from sea) which would prove my hypothesis. To help prove this hypothesis I will also use Spearman’s Rank Coefficient to statistically and numerically show if the correlation is strongly positive, weakly positive, or strongly and weakly negative. This method gives a more accurate insight into what correlation is shown by comparing the data.

My other hypothesis was that where there was more seaweed there were more periwinkles. To prove this I will compare the results of Spearmans Rank Coefficient of percentage seaweed per quadrat and number of periwinkles per quadrat. If the correlation is vaguely the same then the hypothesis will be proven, if it differs then it will be disproved. Also I will use a bar chart with the two sets of data on to further prove this hypothesis. My final hypothesis is that there are fewer limpets where more periwinkles are present, these will also be plotted on a bar chart and spearmans rank will be compared once again.