Category Archives: Statistics

Drug Testing and Statistics


I feel very surprised that people like Lance Amstrong or any other atheletes could by pass the drug test so easily for many years until they got caught. Until recently, I read a blog post about the statistics that reveal the truth about this:

Anti-doping tests have a huge false-negative problem. I have been talking about this for years

As it is a huge false-negative problem, most of the time, the dopers will escape it. But if a player tested positive, it is very high likely that they use doping. It is only somebody suspects and request an official legal and expensive process.

And even if you pass 500 doping test is not an impressive as you thought, more here

The anti-doping agencies are so concerned about not falsely accusing anyone that they leave a gigantic hole for dopers to walk through. . . . While we think about Armstrong’s plight, let’s not forget about this fact: every one of those who now confessed passed hundreds of tests in their careers, just like Armstrong did. In fact, fallen stars like Tyler Hamilton and Floyd Landis also passed lots of tests before they got caught. In effect, dopers face a lottery with high odds of winning and low odds of losing. .

Debt, Inventory and Revenue



Your code is your debt

You spend money, efforts and bug management to control your debt. Code doesn’t automatically generate revenue, user features and user satisfaction do. It doesn’t matter that you write 100 000 lines of code in 10 000 hours and complexity is 1 million (it, well, matters for technical guy) if those efforts doesn’t acquire new users or generate more revenue. It is like saying: I have borrowed 1 million dollars and spent all in this project. It sounds cool but it doesn’t do any benefit to the company. Even worse, it harms the company.


Inventory is what you produce but just sitting on some warehouse/storage and does not generate any money. It could be even worse if it costs you any money to store those things.
Like Joelonsoftware said: inventory can happen in each of the following software process, and they can have different results:

      Decision-Making Process: documentation, product backlog, feature ideas…
      Design Process: diagrams,
      Implementation Process
      Testing Process
      Debugging Process
      Deployment Process

Each of stage’s products can never be implemented, get ignored or become unrealistic the next time. Here, we don’t talk about the waterfall process, which could make it even tremendous. For example, the feature backlog that is written in hundreds of pages that 90% are not implemented. The bug database contains all the bugs, efforts to maintain them and understand them but only 10% of them get fixed after a long time.

As with any kinds of inventories, after a while, your products inside the inventory gets obsolete, and needs cleaning up so the new things can be added in. The obsolete inventories will cost you the efforts and time to create it, maintain it and get rid of it. It is the same for software engineer, the bugs that are no longer bugs (after lots of updates), the features documentation that are not compatible with the current products…

It is important for manager to understand about the similarity of the cost, the debt, the inventory and the revenue in a software engineering process. It is easy to measure engineer by how much code they write, but it is the same as measuring how much debt he brings to the team. Higher debt doesn’t mean higher revenue, so be careful.


Personalization and Price Discrimination

Price Discrimination

Price Discrimination

Since my courses in CMU, I always ask myself if first-degree price discrimination is feasible in e-commerce, and if it is, then how. Anybody knows that the main problem with price discrimination is customers exchange information to each other. And when people know that they are charged differently, they get annoyed.




I just encountered this 2 valuable articles in (Online firms are getting better at calculating how much they can sting you for. Here’s how to pay less) and (How deep are your pockets?). They are explaining to me many good insights, how and what products these firms can charge people differently.

  • Getting your information from cookie, as normal
  • Getting your computer type, if you are an Apple user, you are more likely to pay for higher prices
  • These software can even track your mouse movement

It also explains to me which websites can charge people differently based on no logic. Flight, hotel, secondhand cars and other similar products and services can do this job easily. They already displayed the price sales differently every single day or hour without any complains from the user. With the usage of smartphone, I think this trend will continue when firms have more information and idea about how bad you want their products.

It would be annoyed for any users if they happen to know that they are charged differently just because they are using a Macbook Pro or just because they like the product more than everybody else. I still recommend you to not use this price discrimination strategy intensively but rather to focus on better customer experience. They would help you to do viral marketing and gain more transactions for your company.

Applyzer – more statistics for iPhone Apps

Review example Review example


Just a quick note and introduction over Applyzer : a website that gather all reviews from all countries and rankings of your app in those countries. This is a good thing because iTune does not allow you to view all reviews at the same time and switching the country is so painful that nobody will ever do it. The ranking is also good that let you decide to focus on some countries rather than others if your app requires a little bit localization