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  2. Fermi problem - Wikipedia

    en.wikipedia.org/wiki/Fermi_problem

    An example is Enrico Fermi's estimate of the strength of the atomic bomb that detonated at the Trinity test, based on the distance traveled by pieces of paper he dropped from his hand during the blast. Fermi's estimate of 10 kilotons of TNT was well within an order of magnitude of the now-accepted value of 21 kilotons. [1] [2] [3]

  3. Perimeter - Wikipedia

    en.wikipedia.org/wiki/Perimeter

    The real area is 10,000 2 times the area of the shape on the map. Nevertheless, there is no relation between the area and the perimeter of an ordinary shape. For example, the perimeter of a rectangle of width 0.001 and length 1000 is slightly above 2000, while the perimeter of a rectangle of width 0.5 and length 2 is 5. Both areas are equal to 1.

  4. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    This is a clear trend. ANOVA gives p = 0.091, because the overall variance exceeds the means, whereas linear trend estimation gives p = 0.012. However, should the data have been collected at four time points in the same individuals, linear trend estimation would be inappropriate, and a two-way (repeated measures) ANOVA would have been applied.

  5. Length - Wikipedia

    en.wikipedia.org/wiki/Length

    In an unweighted graph, the length of a cycle, path, or walk is the number of edges it uses. [4] In a weighted graph, it may instead be the sum of the weights of the edges that it uses. [5] Length is used to define the shortest path, girth (shortest cycle length), and longest path between two vertices in a graph.

  6. Power of two - Wikipedia

    en.wikipedia.org/wiki/Power_of_two

    Two to the power of n, written as 2 n, is the number of values in which the bits in a binary word of length n can be set, where each bit is either of two values. A word, interpreted as representing an integer in a range starting at zero, referred to as an "unsigned integer", can represent values from 0 (000...000 2) to 2 n − 1 (111...111 2) inclusively.

  7. Second moment method - Wikipedia

    en.wikipedia.org/wiki/Second_moment_method

    In mathematics, the second moment method is a technique used in probability theory and analysis to show that a random variable has positive probability of being positive. More generally, the "moment method" consists of bounding the probability that a random variable fluctuates far from its mean, by using its moments.

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