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For those who can't see the image, the XX-plane is just the number line. The x-axis can't be intersected by parallel lines that don't intersect the x-axis or have it as a component of the relative complement (by symmetry).
Any nice polynomial resembles a dragon because it shifts nicely on the R2-plane. The R2-plane is a great place to start with images.
The tautochrone, an advanced linear reduction of the respective derivatives was proposed by a certain great mathematician to explain a primitive image of space-time. In the projected challenge, the great mathematician asked inquiring minds to explain why the objects' curve represented a higher velocity outcome than a variety of line segments constructed by nothing but gravity and acceleration.
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For those who were interested in my previous remark about the uniform normal dichotomy reflect on your perception of the steadfastness of daily life. Every distribution (including the Poisson distribution) is present in our daily life. For fans of statistics, make sure your introductory student identifies the commonality between the Chi-square distribution and gamma distribution (Monte Carlo simulation is like bootstrapping with a magnet). Anyway, it is really hallucinogenic to reflect on the uniformity of cause and time and how the refraction of variables causes almost no noise (but only the perception of error uniformity).
Fans of the annihilation matrix and linear algebra might remember this famous hit by Peter, Paul, & Mary. What is the mysterious underpinning of best reduction as a linear form? Well, a sort of pointillism highlighting the sort pick-ups sticks mash up linear identification. How do we identify a specific point of light above our head as distinct from a receding line? Well, light of course, and so the dragon is complete.
