"No one is harder on a talented person than the person themselves" - Linda Wilkinson ; "Trust your guts and don't follow the herd" ; "Validate direction not destination" ;

May 03, 2016

Day #19 - Probability Basics

  • Events - Subset of Sample Space
  • Sample Space - Set of all possible outcomes
  • Random Variable - Outcome of experiment captured by Random variable
  • Permutation - Ordering matters
  • Combination - Ordering does not matter
  • Binomial - Only two outcomes of trail
  • Poisson - Events that take place over and over again. Rate of Event denoted by lambda
  • Geometric - Suppose you'd like to figure out how many attempts at something is necessary until the first success occurs, and the probability of success is the same for each trial and the trials are independent of each other, then you'd want to use the geometric distribution
  • Conditional Probability - P(A Given B) = P(A) will occur assume B has already occurred
  • Normal Distribution - Appears because of central limit theorem (Gaussian and Normal Distribution both are same)
From Quora -  
"Consider a binomial distribution with parameters n and p. The distribution is underlined by only two outcomes in the run of an independent trial- success and failure. A binomial distribution converges to a Poisson distribution when the parameter n tends to infinity and the probability of success p tends to zero. These extreme behaviours of the two parameters make the mean constant i.e. n*p = mean of Poisson distribution "

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