For the R code:
x4 = runif(250,0,99)
y4 = rnorm(250,50,15)
mypoints = cbind(x4,y4)
write.csv(mypoints,file="mypoints.csv")
The points are a combination of a unifrom and a normal distribution.
Patterns: The 'broad' distribution is captured in each figure, a central density running down the center with slight skew to the top. However, at each rescaling from 3x3 to 25x25 the detail of the distribution changes. At 3x3 to 10x10, depending on what type of conclusions we are trying to draw from the information, our level of precision is increasing, however, we may not necessarily be making false inferences.
Rather counter-intuitively the possibility of error seems to increase at the higher detail.
. . . . continuing
x4 = runif(250,0,99)
y4 = rnorm(250,50,15)
mypoints = cbind(x4,y4)
write.csv(mypoints,file="mypoints.csv")
The points are a combination of a unifrom and a normal distribution.
Patterns: The 'broad' distribution is captured in each figure, a central density running down the center with slight skew to the top. However, at each rescaling from 3x3 to 25x25 the detail of the distribution changes. At 3x3 to 10x10, depending on what type of conclusions we are trying to draw from the information, our level of precision is increasing, however, we may not necessarily be making false inferences.
Rather counter-intuitively the possibility of error seems to increase at the higher detail.
. . . . continuing
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