Since today, 19 Sept is talk like a pirate day, I would like to relate a story about stats and pirates. While driving, my wife was in the back seat with our young child asked me how to draw a pirate hat. Since I was driving I could not show her ... [Read more...]

For those who have been following the R-Bloggers this picture should be yesterdays news, but there was an article on the BBC on it, full story HERE. I find it interesting how it was on Drudge Report (www.drudgereport.com) which gets over 1 million hits... [Read more...]

This is the second part of the forecasting exercise, where I am looking at a multiple regression. To keep it simple I chose the states that boarder WI and the US unemployment information for the regression. Again this is a down and dirty analysis, I wo... [Read more...]

I wanted to see what I could do in a hurry using the commands found at Forecasting: Principles and Practice . I chose a simple enough data set of Wisconsin Unemployment from 1976 to the present (April 2013). I kept the last 12 months worth of... [Read more...]

With all the cleaning done, the only thing left to do is save the data to be analyzed, for future use, and I hope by others. The data I thought would be simple, but there were a few interesting twist, like the Primary Credit*, and using ifelse() to edi... [Read more...]

The blog in the data cleaning series looks at separating out the Federal Reserve Districts. What I wanted was two additional columns, where I had the name of the city and the number for each district. Since I was on a separation kick I thought it would... [Read more...]

So far the individual files have been left on their own, it is now time to combine using the rbind function, simple enough after all we have done so far, then the quick check with summary.Now that we have one data frame, time to make larger changes to ... [Read more...]

Building on the previous posts (post 1 & post 2) I found there were 12 instances with the type of credit where there was a "Primary*" which means the lender borrowed twice in the same day, in the 2010 q4 data. It would seem simple enough in Excel, ... [Read more...]

The first post (found here) we downloaded the data and imported it to R using the gdata package. This post we will be changing the column names to make them more reasonable, and adding a quarter variable. The reason for changing the column names is bec... [Read more...]

With spring in the air, I thought it would be fun to do a series on (spring) cleaning data. The posts will follow my efforts to to download the data, import into R, cleaned it up, merge the different files, add columns of information created, and then ... [Read more...]

The second community event is the Soldier Hollow Junior Olympics (SoHo), again found in the Heber Valley area. Building upon the previous posts (part 1 and part 2) this one will show an event that has more people coming from greater distance. Take the bar charts for the number of participants and ... [Read more...]

This post will examine the Heber Valley Railroad, a small town tourist attraction using event gravitational pull. Using the information from part 1 the two factors associated with the events gravity, the number of participants, and the distance they traveled. The number of participants can be shown using bar charts, histograms, ... [Read more...]

About 8 years ago, I was sitting in class listening to a guest lecturer talk about how community events can be described like celestial bodies with their own gravity, where the size and importance of the event would attract more people, from farther away. Much like a black hole, where the ... [Read more...]

This is the start of analyzing the Federal Reserve and Banking data mentioned in my "A Christmas Miracle". The file is a combination of summary data and actual data from each of the 400+ banks that recieved funds from the Federal Reserve during 2007-20... [Read more...]

Data files on 407 banks, between the dates of 2007 to 2009, on the daily borrowing with the US Federal Reserve bank. The data sets are available from Bloomberg at this address data This is an unprecedented look into the day-to-day transactions of ... [Read more...]

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When learning R it is helpful to have your own personal help file. One you create for yourself, with the notes, links, and language you understand (sometimes the help files are not very helpful). Let me introduce you to Tomboy Notes.Tomboy Notes is a l... [Read more...]

Disclaimer: All prices and classes are approximate and should be confirmed at www.statistics.com as they can change. A comment from my previous post asked me about the experience I had in taking courses from statistics.com (www.statistics.com). To help... [Read more...]

Opening this blog is a step in a long journey of discovery, learning and frustration. To begin with I would consider myself a beginner R user, I am getting better, but I am not about to write a package any time soon. I started using R about three years... [Read more...]