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The chance the family consists of a boy and a girl is 14 / 27 , about 0.52. This variant of the boy and girl problem is discussed on many internet blogs and is the subject of a paper by Ruma Falk. [13] The moral of the story is that these probabilities do not just depend on the known information, but on how that information was obtained.
Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes.Two events are independent, statistically independent, or stochastically independent [1] if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect the odds.
Independent: Each outcome of the die roll will not affect the next one, which means the 10 variables are independent from each other. Identically distributed: Regardless of whether the die is fair or weighted, each roll will have the same probability of seeing each result as every other roll. In contrast, rolling 10 different dice, some of ...
(That is, the two dice are independent.) If, however, the 1st die's result is a 3, and someone tells you about a third event - that the sum of the two results is even - then this extra unit of information restricts the options for the 2nd result to an odd number. In other words, two events can be independent, but NOT conditionally independent. [2]
Odds of having identical quadruplets are about one in 15 million — which makes Mercedes and Jonathan Sandhu, and their four identical daughters, very special.
Students of statistics and probability theory sometimes develop misconceptions about the normal distribution, ideas that may seem plausible but are mathematically untrue. For example, it is sometimes mistakenly thought that two linearly uncorrelated, normally distributed random variables must be statistically independent.
The little girl did a double-take when she met her uncle. Baby girl meets dad’s identical twin and can’t tell them apart: ‘Two dadas!’ Skip to main content
The independent samples t-test is used when two separate sets of independent and identically distributed samples are obtained, and one variable from each of the two populations is compared. For example, suppose we are evaluating the effect of a medical treatment, and we enroll 100 subjects into our study, then randomly assign 50 subjects to the ...