15
Mar 16

## Probability Podcast Ep2: Imprecise probabilities with Gert de Cooman

I happened to be travelling through Brussels, so I stopped by Ghent, the world hotspot for research into imprecise probabilities, and setup an interview with Gert de Cooman. Gert has been working in imprecise probabilities for more than twenty years, is a founding member and former President of SIPTA, the Society for Imprecise Probability: Theories and Applications, and has helped organize many of the ISIPTA conferences and SIPTA Schools.

Topics include fair betting rates, Dutch books, Monte Carlo methods, Markov chains, utility, and the foundations of probability theory. We had a rich, wide-ranging discussion. You may need to listen two (or more!) times to process everything.

Episode on SoundCloud

12
Jun 14

## A new way to visualize content

Right now I’m working on a project that involves new ways to view units of content and the relationships between them. I’ve posted the comic I worked on, it has a number of stats references throughout. This is early alpha stages for the software, you may run into issues. To see the relationships, go to the puffball menu and make sure that “Show relationships” is clicked.

14
Feb 13

## Population simulation leads to Valentine’s Day a[R]t

Working on a quick-and-dirty simulation of people wandering around until they find neighbors, then settling down. After playing with the coloring a bit I arrived at the above image, which I quite like. Code below:

```# Code by Matt Asher for statisticsblog.com # Feel free to modify and redistribute, but please keep this notice   maxSettlers = 150000   # Size of the area areaW = 300 areaH = 300   # How many small movements will they make to find a neighbor maxSteps = 200   # Homesteaders, they don't care about finding a neighbor numbHomesteaders = 10   areaMatrix = matrix(0, nrow=areaW, ncol=areaH)   # For the walk part adjacents = array(c(1,0,1,1,0,1,-1,1,-1,0,-1,-1,0,-1,1,-1), dim=c(2,8))   # Is an adjacent cell occupied? hasNeighbor <- function(m,n,theMatrix) { toReturn = FALSE for(k in 1:8) { yCheck = m + adjacents[,k][1] xCheck = n + adjacents[,k][2] if( !((xCheck > areaW) | (xCheck < 1) | (yCheck > areaH) | (yCheck < 1)) ) { if(theMatrix[yCheck,xCheck]>0) { toReturn = TRUE } } } return(toReturn) }     # Main loop for(i in 1:maxSettlers) { steps = 1 xPos = sample(1:areaW, 1) yPos = sample(1:areaH, 1)   if(i <= numbHomesteaders) { # Seed it with homesteaders areaMatrix[xPos,yPos] = 1 } else { if(areaMatrix[xPos,yPos]==0 & hasNeighbor(xPos,yPos,areaMatrix)) { areaMatrix[xPos,yPos] = 1 } else { spotFound = FALSE outOfBounds = FALSE   while(!spotFound & !outOfBounds & (steps<maxSteps)) {   # Look for a new location in one of adjacent 9 cells, while still in area steps = steps + 1 movement = adjacents[,sample(1:8,1)] xPos = xPos + movement[1] yPos = yPos + movement[2]   if( (xPos > areaW) | (xPos < 1) | (yPos > areaH) | (yPos < 1)) { outOfBounds = TRUE } else if(hasNeighbor(xPos,yPos,areaMatrix) ) { areaMatrix[xPos,yPos] = steps spotFound = TRUE } } }   }   }   image(areaMatrix, col=rev(rgb(seq(0.01,1,0.01),seq(0.01,1,0.01),seq(0.01,1,0.01))))   # I think this version looks nicer! # areaMatrix[areaMatrix !=0] = 1 # image(areaMatrix, col=rev(rgb(.5,0,seq(0.2,1,0.2))))```

14
Dec 12

## Let it snow!

A couple days ago I noticed a fun piece of R code by Allan Roberts, which lets you create a digital snowflake by cutting out virtual triangles. Go give it a try. Roberts inspired me to create a whole night sky of snowflakes. I tried to make the snowfall look as organic as possible. There are lots of options to adjust. Here’s the code, have fun and Happy Holidays!

```# Code by Matt Asher for statisticsblog.com # Feel free to modify and redistribute   # How many flakes do you want to fall? flakes = 100   # Width and height of your space width = 800 height = 600   # Initial wind wind = 0   # Setup the background of the plot and margins par(bg = "black") par(oma=c(0,0,0,0)) par(mar=c(0,0,0,0)) plot(0, 0, col="black", pch=".", xlim=c(0,width), ylim=c(0,height), axes=F)   for(i in 1:flakes) { startY = height startX = runif(1,1,width)   xPos = startX yPos = startY   for(j in 1:height) {   # Optional drift in wind wind = wind + rcauchy(1,0,.05)   # Update snowflake position xPos = xPos + rnorm(1,.1,1.5) yPos = yPos - runif(1,4,20)   # Are we in the space, if so display it if(xPos &gt; 0 &amp;&amp; xPos &lt;= width &amp;&amp; yPos &gt; 0 &amp;&amp; yPos &lt;= height) { points(round(xPos), round(yPos), col="white", pch=8)   # System dely, slows down the flakes Sys.sleep(0.1) } } }```

23
Oct 12

## Comic with stats discussion

I recently finished work on the first issue of a graphic novel. It’s in the form of a fictional first person narrative. The story isn’t directly about statistics, but there are a few digressions on the subject. Here are some samples, make sure to click on the images for a larger view:

If you’re interested, head over to sunfalls.com and pick up a copy. Here’s the order page. The comic comes with a full money-back guarantee, including shipping. You don’t even have to send back your copy to claim the refund.