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A good way to understand the Binomial distribution is to consider the following problem You are given a worn and bent coin and asked to estimate the probability that the coin will turn up heads when tossed Let us call this unknown probability of heads p You toss the coin n times and record the number of times r that it turns up heads A reasonable estimate of p is rln Note that if the experiment were rerun, generating a new set of n coin tosses, we might expect the number of heads r to vary somewhat from the value measured in the first experiment, yielding a somewhat different estimate for p The Binomial distribution describes for each possible value of r (ie, from 0 to n), the probability of observing exactly r heads given a sample of n independent tosses of a coin whose true probability of heads is p Interestingly, estimating p from a random sample of coin tosses is equivalent to estimating errorv(h) from testing h on a random sample of instances A single 3 toss of the coin corresponds to drawing a single random instance from 2 and determining whether it is misclassified by h The probability p that a single random coin toss will turn up heads corresponds to the probability that a single instance drawn at random will be misclassified (ie, p corresponds to errorv(h)) The number r of heads observed over a sample of n coin tosses corresponds to the number of misclassifications observed over n randomly drawn instances Thus rln corresponds to errors(h) The problem of estimating p for coins is identical to the problem of estimating errorv(h) for hypotheses The Binomial distribution gives the general form of the probability distribution for the random variable r, whether it represents the number of heads in n coin tosses or the number of hypothesis errors in a sample of n examples The detailed form of the Binomial distribution depends on the specific sample size n and the specific probability p or errorv(h) The general setting to which the Binomial distribution applies is: 1 There is a base, or underlying, experiment (eg, toss of the coin) whose outcome can be described by a random variable, say Y The random variable Y can take on two possible values (eg, Y = 1 if heads, Y = 0 if tails) 2 The probability that Y = 1 on any single trial of the underlying experiment is given by some constant p, independent of the outcome of any other experiment The probability that Y = 0 is therefore (1 - p) Typically, p is not known in advance, and the problem is to estimate it 3 A series of n independent trials of the underlying experiment is performed (eg, n independent coin tosses), producing the sequence of independent, identically distributed random variables Y l , Yz, , Yn Let R denote the number of trials for which Yi= 1 in this series of n experiments. create qr code in c# c# 使用ThoughtWorks.QRCode.dll生成二维码图片- lwpoor123的博客 ...
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Nov 1, 2017 · In this article you will learn how to generate QR Code in C#. ... Create a Windows Form Application project in VS, add the dll to your . Audio Engineering Society (AES)/AES Standards Committee (AESSC) wwwaesorg 60 E 42nd St New York, NY 10165-2520 212-661-8528, fax 212-682-0477 American National Standards Institute (ANSI) wwwansiorg 11 West 42nd Street New York, NY 10036 212-642-4900, fax 212-398-0023 Commission Internationale de l clairage/International Commission on Illumination (CIE) ciecb@pingat IE Central Bureau, Kegelgasse 27 A-1030 Vienna, Austria 43 (01) 714 31 87/0 , fax 43 (01) 713 0838/18 Deutsches Institut f r Normung/German Institute for Standardization (DIN) wwwdinde, postmaster@dinde Burggrafenstrasse 6, D-10787 Berlin, Germany 49 30 26 01-0, fax 49 30 26 01 12 31 European Telecommunications Standards Institute (ETSI) wwwetsifr Route des Lucioles, F-06921 Sophia Antipolis, Cedex, France 33 4 92 94 42 00, fax 33 4 93 65 47 16 European Broadcasting Union (EBU) wwwebuch qr code generator c# C# Tutorial - Generate QR Code | FoxLearn - YouTube
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A pure C# Open Source QR Code implementation. ... Over 36 million developers use GitHub together to host and review code, project manage, and build software .... You only need five lines of code, to generate and view your first QR code. European Computer Manufacturers Association (ECMA) wwwecmach, helpdesk@ecmach 114 Rue de Rh ne, CH-1204 Gen ve 20, Switzerland 41 22 735 3634 International Electrotechnical Commission (IEC) wwwiecch 3 rue de Varemb , Case postale 131 1211 Gen ve 20, Switzerland 41 22 919 02 11, fax 41 22 919 03 00 International Organization for Standardization (ISO) wwwisoch, central@isoch 1 rue de Varemb , Case postale 56 CH-1211 Gen ve 20, Switzerland 41 22 749 01 11, fax 41 22 733 34 30 International Telecommunication Union (ITU) wwwituint, sales@ituint Sales Service Place de Nations CH-1211 Gen ve 20, Switzerland 4 The probability that the random variable R will take on a specific value r (eg, the probability of observing exactly r heads) is given by the Binomial distribution n! Pr(R = r ) = pr(l - p)"-' r!(n - r ) ! A plot of this probability distribution is shown in Table 53 Listing 10-5 41 22 730 6141 (English), 41 22 730 6142 (French), 41 22 730 6143 (Spanish), fax 41 22 730 5194 National Committee for Information Technology Standards (NCITS) (Formerly the Accredited Standards Committee X3, Information Technology) wwwncitsorg Optical Storage Technology Association (OSTA) wwwostaorg 311 E Carrillo St Santa Barbara, CA 93101 805-962-1541 c# print qr code The C# Barcode and QR Library | Iron Barcode - Iron Software
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