A view of the cover of a 'sanitary sewer,' (and why would you want any other kind?!). And as promised last week, notice the accumulation of pine needles around the edge of the cover. On this day the wind was quite gusty, blowing along this sidewalk from the bottom of the image to the top. Due to this wind direction, many more pine needles have accumulated and piled up around the cover at the bottom than at the top. This forms a histogram of the frequency distribution of wind action distributed around the circumference of the sewer cover.
If we had data situated around the circumference of a circle we could display it as a circular dot plot as shown below from the book "Circular Statistics" by Fisher. These are arrival times, on a 24hr clock, are for 254 patients at an intensive care unit. Few arrive in the morning, many more arrive in late afternoon and early evening.
An estimate of the density of circular sample can be computed using something like the code for a circular density curve in the programming language R, as shown below.
Such graphical tools are the beginnings of modeling on spheres and other manifolds studied under the general heading of directional statistics.
A probability density function defined on the real line is sometimes wrapped around a circle. We have earlier seen that the results of such wrapping give rise to the characteristic function, a fundamental tool of probability modeling.
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