hypergeometric probability function

3.1 Two-Point Distribution and even distribution1. Two-Point DistributionMany random events have only two results. If the result of the product is qualified or unqualified, the product or reliable work may fail. This type of random event variable

1. Concept of Random Variables As the name implies, a random variable is a variable with a random value. The opposite of a random variable is a "deterministic variable", that is, the variable whose value follows a certain strict rule, such as the

The stat2.2x probability (probability) course was taught at the EdX platform in 2014 by the University of California, Berkeley (University of California, Berkeley).Download PDF Note (academia.edu)ADDITIONAL Practice for the FINALProblem 1A box

Chapter I. Stochastic events and probabilitiesChapter two stochastic variables and their distributionsChapter three multivariate random variables and their distributionsThe fourth chapter law of large numbers and the central limit theoremThe fifth

This document is a PDF format directly converted from the Internet, Introduction to MATLAB mathematical statistics toolbox1. OverviewThe Mathematical Statistics toolbox of MATLAB is a relatively simple tool in the MATLAB toolbox. The mathematical

Discrete variable refers to the variable can only take discrete isolated values, usually by the number of units of measurement, such as number, number of units. Many of the distributions of discrete variables are related to last, so let's take a

Common Data Mining & machine learning knowledge (points)Basis (Basic):MSE (meansquare error mean square), LMS (Least meansquare min-squared), LSM (Least square Methods least squares), MLE (Maximum Likelihoodestimation Maximum likelihood estimation),

Documents translated from the official website. Transfer from http://www.mamicode.com/info-detail-507676.htmlRandom Sampling (Numpy.random) Simple Random data Rand (D0, D1, ..., DN) Random values>>> Np.random.rand (3

The accord.net framework is encapsulated and further developed on the basis of the Aforge.net project. Because Aforge.net focuses more on the underlying and breadth, the accord.net framework focuses more on machine learning algorithms and solutions

Basis (Basic):MSE (Mean square error mean squared error), LMS (leastmean square min squared), LSM (Least square Methods least squares), MLE (Maximumlikelihood Estimation maximum likelihood estimation), QP (quadratic programming two-time plan), CP