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Home > Art, Film & Photography > Probability Distributions: Probability Distribution, Hubbert Curve, Weibull Distribution, Cumulative Frequency Analysis, Mixture Distribution
Probability Distributions: Probability Distribution, Hubbert Curve, Weibull Distribution, Cumulative Frequency Analysis, Mixture Distribution

Probability Distributions: Probability Distribution, Hubbert Curve, Weibull Distribution, Cumulative Frequency Analysis, Mixture Distribution


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About the Book

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 25. Chapters: Probability distribution, Hubbert curve, Weibull distribution, Cumulative frequency analysis, Mixture distribution, Tracy-Widom distribution, Tweedie distributions, Compound probability distribution, Rank-size distribution, Compound Poisson distribution, Beta prime distribution, Folded normal distribution, Cantor distribution, Bimodal distribution, Von Mises-Fisher distribution, Kent distribution, Ewens's sampling formula, Location-scale family, Free Poisson distribution, Marchenko-Pastur distribution, Half-normal distribution, Crystal Ball function, Credal set, Bhatia-Davis inequality, Factorial moment, Bingham distribution, Singular distribution, Popoviciu's inequality on variances, Log-Laplace distribution, Consumption distribution, Relationships among probability distributions, Null distribution. Excerpt: In probability theory and statistics, the Weibull distribution is a continuous probability distribution. It is named after Waloddi Weibull who described it in detail in 1951, although it was first identified by Frechet (1927) and first applied by Rosin & Rammler (1933) to describe the size distribution of particles. The probability density function of a Weibull random variable x is: where k > 0 is the shape parameter and >0 is the scale parameter of the distribution. Its complementary cumulative distribution function is a stretched exponential function. The Weibull distribution is related to a number of other probability distributions; in particular, it interpolates between the exponential distribution (k = 1) and the Rayleigh distribution (k = 2). If the quantity x is a "time-to-failure," the Weibull distribution gives a distribution for which the failure rate is proportional to a power of time. The shape parameter, k, is that power plus one, and so this parameter can be interpreted directly as follows...


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Product Details
  • ISBN-13: 9781156574171
  • Publisher: Books LLC, Wiki Series
  • Publisher Imprint: Books LLC, Wiki Series
  • Height: 246 mm
  • No of Pages: 26
  • Spine Width: 1 mm
  • Weight: 68 gr
  • ISBN-10: 115657417X
  • Publisher Date: 04 Sep 2011
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: Probability Distribution, Hubbert Curve, Weibull Distribution, Cumulative Frequency Analysis, Mixture Distribution
  • Width: 189 mm


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