In the first part of this post we considered a human-based binary random numbers generator and built a predictive model for it. The model appeared to work better than a coin toss, at least for a short sequence we had. This part develops more complex models with somewhat higher accuracy. Continue reading Prediction of random numbers. Part 2

# Tag Archives: sampling

# Prediction of random numbers. Part 1

What is a chance to guess a random number? For zero-or-one guessing 50% seems like a fair estimate. But what if you know that source of randomness is a human being? Continue reading Prediction of random numbers. Part 1

# Sampling and common sense

Suppose that you are provided with two binary sequences {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1} and {0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0}. Which one is more likely to be generated by tossing a coin (i.e. a Bernoulli process with 0.5 probability of event occurrence)? Continue reading Sampling and common sense