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Effect of trampling on length of Cranesbill leaves - Coursework Example

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Effect of Trampling on the Length of Cranesbill Leaves Table of Contents Interpretation 3 Evaluation 6 References 8 Interpretation We get the mean and standard deviation again for the main results, and come up with the table below. The standard deviation of the lengths of the leaves may be significant in determining the validity of the sample data, as well as provide insights into the nature of the samples and the sampling area (Statistics Canada 2011; Wolfram Research 2012) …
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Effect of trampling on length of Cranesbill leaves
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Download file to see previous pages We make the assumption, for instance, that for a given distance along the transect, the soil and other relevant conditions are similar. Moreover, we can take it that if the data is any good, then standard deviations along any point of data collection along the transect (one meter intervals) should be small. This is to be expected too, given that for every measurement point along the transect there is only one reading for the soil compaction level, and several readings for the leaf length. Therefore, if soil compaction is correlated with the leaf length, then one can assume that the variations in length sizes along any measurement point in the transect should be small, or at least not significant enough to cause worry and doubt as to the validity of the data and of the alternative hypothesis being accepted (Statistics Canada 2011). Indeed, looking at the range of the standard deviation along the different measurement points in the transect, one sees that there is somewhat of a variation along the measurement points, by a factor of 3 in some measurement points compared to others. There are several ways to interpret this. On the one hand, looking at the standard deviation figures, within the measurement points it is not conclusive that the standard deviation magnitudes are enough to cause worry as to the data validity. On the other hand, one can also investigate that maybe the wide variances in the sample data of leaf lengths within the measurement points may have something to do with the standard deviation being large or small. For example, looking at measurement point 8, or the measurement of leaf lengths at the point of eight meters from the start of the transect, one sees that the standard deviation is unusually large, in fact larger than any other standard deviation figure for the rest of the measurement points. Examining the data for this measurement point, one sees that compared to the other measurement points, there is a wider variation of measurement data for leaf lengths (1.5; 2.8; 2.8; 2.7; 2.3; 2.5). Looking at the measurements of leaf lengths at point 0, where the transect begins, one sees that the variation in measurements is somewhat smaller, or to put it another way, the leaf lengths are closer to each other, or varies less in comparison to measurement point 8 (1, 0.8; 0.8; 0.7; 0.7). This is borne out by the computed standard deviation for this measurement point, which is about a factor of three smaller than the standard deviation for point 8. The point is that within the measurement points, the standard deviation for the measurements vary in magnitude, and in some measurement points quite larger in comparison to the other measurement points. Judging by the standard deviation alone therefore, one comes to suspect whether the correlation between soil compaction and leaf length exists, and if the established correlation is valid. Of this, more will be said with regard to the inherent limitation of the study (Statistics Canada 2011; Wolfram Research 2012) Looking at ambient data, or data that is related to soil quality or pH, soil temperature, and the amount or intensity of the light present, this paper makes the assumption that more study needs to be done to either factor in or discount each of these variables as being correlated or associated with leaf length. ...Download file to see next pagesRead More
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