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  2. Probability bounds analysis - Wikipedia

    en.wikipedia.org/wiki/Probability_bounds_analysis

    At about the same time, Makarov, [6] and independently, Rüschendorf [7] solved the problem, originally posed by Kolmogorov, of how to find the upper and lower bounds for the probability distribution of a sum of random variables whose marginal distributions, but not their joint distribution, are known.

  3. Concentration inequality - Wikipedia

    en.wikipedia.org/wiki/Concentration_inequality

    Chebyshev's inequality requires the following information on a random variable : . The expected value ⁡ [] is finite.; The variance ⁡ [] = ⁡ [(⁡ [])] is finite.; Then, for every constant >,

  4. Quizlet - Wikipedia

    en.wikipedia.org/wiki/Quizlet

    Quizlet is a multi-national American company that provides tools for studying and learning. [1] Quizlet was founded in October 2005 by Andrew Sutherland, who at the time was a 15-year old student, [ 2 ] and released to the public in January 2007. [ 3 ]

  5. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  6. Percentile rank - Wikipedia

    en.wikipedia.org/wiki/Percentile_rank

    Occasionally the percentile rank of a score is mistakenly defined as the percentage of scores lower than or equal to it [citation needed], but that would require a different computation, one with the 0.5 × F term deleted. Typically percentile ranks are only computed for scores in the distribution but, as the figure illustrates, percentile ...

  7. Interquartile range - Wikipedia

    en.wikipedia.org/wiki/Interquartile_range

    The lower quartile corresponds with the 25th percentile and the upper quartile corresponds with the 75th percentile, so IQR = Q 3 − Q 1 [1]. The IQR is an example of a trimmed estimator , defined as the 25% trimmed range , which enhances the accuracy of dataset statistics by dropping lower contribution, outlying points. [ 5 ]

  8. Universal Soil Loss Equation - Wikipedia

    en.wikipedia.org/wiki/Universal_Soil_Loss_Equation

    The Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes soil erosion processes. [1]Erosion models play critical roles in soil and water resource conservation and nonpoint source pollution assessments, including: sediment load assessment and inventory, conservation planning and design for sediment control, and for the advancement of scientific understanding.

  9. Boole's inequality - Wikipedia

    en.wikipedia.org/wiki/Boole's_inequality

    P( at least one estimation is bad) = 0.05 ≤ P( A 1 is bad) + P( A 2 is bad) + P( A 3 is bad) + P( A 4 is bad) + P( A 5 is bad) One way is to make each of them equal to 0.05/5 = 0.01, that is 1%. In other words, you have to guarantee each estimate good to 99%( for example, by constructing a 99% confidence interval) to make sure the total ...