I have decided to apply predictive analytics to see if James is going to post a blog entry today. (James tell me his first post this morning "wasn't much of a post", so we'll assume for our purposes that one doesn't count.)
Unfortunately, I did not have sufficient empirical evidence to apply standard statistical methods. Instead, I've had to rely on expert judgment to create a scorecard that will allow me to assess the likelihood that he will post.
I considered a variety of factors that probably come into play, such as whether or not he's nearing his book deadline, whether his mummy is visiting from England, and whether he can go outside to play cricket in relatively warm weather. Each of the potential values has been "binned", or sorted into ranges of values, and I have assigned a value to each bin: the larger the score, the more likely he is to blog!
When I take the conditions on any given day, and sum up all the associated scores, I have found that if the number exceeds 90, then he will blog. That means, I also have a simple rule: "If James's blog likelihood score is 89 or less, then I must post a blog entry, to fill the void."
Today, I found that his blogging score DID NOT exceed that value - primarily because his book is due IMMINENTLY. So, it looks like it's going to be up to me for much of this week. So, here goes...