# I am too new for words

##### New Member
Ok, I am quite new to statistical analysis and will be training myself. I am working in Quality Assurance at a nuclear site.
Here is the premise:
Many models of issue deficiencies us a "Bird's Triangle" model. Industrial Safety for example. In each tier of blocks the numbers change to indicate the number of incidences that rise to a level of severity. If the top block in a triangle is a fatality on the job, the next tier down will be, say 6 instances where the worker is transported to medical attention with a lost-time injury. The tier below that might be 30 occurrences of first aid given on site, and below that a tier of near-misses numbering maybe 300.

What I am not sure of is the statistical validity of using the model as a predictor of future occurrence. I wonder if the "Gambler's Fallacy" is true here. To explain:

If I am near the top of the safety model I described, that I have 6 recorded injuries in a year or so then the "appearance" is that we are doomed to have a fatality in the near future. I know that that is not true. The Gambler fallacy notes that flipping a coin 6 times for heads does not make it more likely that the 7th will be tails, it is still 50/50.
So statistically the ratio of next-to -top tier and top tier is more of a statistical "warning"? That given a very large dataset the ratio will hold true? How can I demonstrate the reality and both caution against complacency and not calling the sky to fall?