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I am looking for a way to test a hypothesis;

"the closer my point feature is to my line feature (both vector), the higher the score of C will be"

(for other sections of my research so far I have looked at overall density of my points using heatmap, and at the distance from line features using the distance matrix) for this stage so far i have created a weighted heatmap based on the score of C in my database, but i don't know how to relate this to my line data my desktop currently looks like this: enter image description here

a look at other questions seems to suggest using interpolation but i'm not entirely sure how this works, i used the method to produce the image in the picture above but i dont know how to interpret it

so any ideas how to present weighted attribute data and relate it to my line data? if interpolation is the answer, links to description of interpolation in laymans terms are requested. am using qgis 2.10

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So I suppose this is not a typical thing that people do on QGIS, anyway eventually I performed the heatmap function using weighted attribute data base on my score of C. then calculated and vectorised the raster so that it showed clusters of C. I'm now discussing these in my thesis in terms of what can be shown (rather than scientifically calculated) along with previous results of an earlier distance matrix. I'm sure there is a better (read more scientific) way of doing this, but as i'm constrained by time right now this approach is sufficient.

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