https://blog.csdn.net/tangbin330zh-cnhttps://blog.csdn.net/https://blog.csdn.net/tangbin330/article/details/9203947https://blog.csdn.net/tangbin330/article/details/9203947tangbin330Sat, 29 Jun 2013 18:26:42 +0800https://blog.csdn.net/tangbin330/article/details/9192049https://blog.csdn.net/tangbin330/article/details/9192049tangbin330Thu, 27 Jun 2013 22:26:41 +0800https://blog.csdn.net/tangbin330/article/details/9189621https://blog.csdn.net/tangbin330/article/details/9189621tangbin330Thu, 27 Jun 2013 16:58:58 +0800https://blog.csdn.net/tangbin330/article/details/9132329https://blog.csdn.net/tangbin330/article/details/9132329tangbin330Wed, 19 Jun 2013 21:31:03 +0800https://blog.csdn.net/tangbin330/article/details/9128765https://blog.csdn.net/tangbin330/article/details/9128765tangbin330Wed, 19 Jun 2013 14:47:57 +0800https://blog.csdn.net/tangbin330/article/details/9127467https://blog.csdn.net/tangbin330/article/details/9127467tangbin330Wed, 19 Jun 2013 14:21:44 +0800https://blog.csdn.net/tangbin330/article/details/9123985https://blog.csdn.net/tangbin330/article/details/9123985tangbin330Tue, 18 Jun 2013 21:24:29 +0800https://blog.csdn.net/tangbin330/article/details/9114925https://blog.csdn.net/tangbin330/article/details/9114925tangbin330Mon, 17 Jun 2013 19:12:53 +0800https://blog.csdn.net/tangbin330/article/details/9105957https://blog.csdn.net/tangbin330/article/details/9105957tangbin330Sun, 16 Jun 2013 14:45:22 +0800https://blog.csdn.net/tangbin330/article/details/9105061https://blog.csdn.net/tangbin330/article/details/9105061tangbin330Sun, 16 Jun 2013 11:43:11 +0800https://blog.csdn.net/tangbin330/article/details/8805152https://blog.csdn.net/tangbin330/article/details/8805152tangbin330Mon, 15 Apr 2013 18:29:15 +0800https://blog.csdn.net/tangbin330/article/details/8802580https://blog.csdn.net/tangbin330/article/details/8802580tangbin330Mon, 15 Apr 2013 10:32:47 +0800https://blog.csdn.net/tangbin330/article/details/8802450https://blog.csdn.net/tangbin330/article/details/8802450tangbin330Mon, 15 Apr 2013 09:56:57 +0800https://blog.csdn.net/tangbin330/article/details/8798033https://blog.csdn.net/tangbin330/article/details/8798033tangbin330Sat, 13 Apr 2013 20:37:28 +0800https://blog.csdn.net/tangbin330/article/details/8747420https://blog.csdn.net/tangbin330/article/details/8747420tangbin330Mon, 01 Apr 2013 16:49:32 +08000，p1+p2+...+pn=1。现将试验独立重复N次，以Xi记为在N次试验中事件Ai出现的次数，X=(X1,X2,...,Xn)为n维随机向]]>https://blog.csdn.net/tangbin330/article/details/8746937https://blog.csdn.net/tangbin330/article/details/8746937tangbin330Mon, 01 Apr 2013 15:53:10 +08000且为一常数。 泊松分布多出现在当X表示在一定时间或者空间内罕见事件出现个数的场合。它是二项分布样本空间趋于无限，事件A发生概率p较小时的推导。 泊松分布的推导 假设某一时间段内，某交通路口发生事故的概率是p，为求该时间段内交通路口发生的事故个数。假设所观察的时间为]]>https://blog.csdn.net/tangbin330/article/details/8746692https://blog.csdn.net/tangbin330/article/details/8746692tangbin330Mon, 01 Apr 2013 15:12:26 +0800https://blog.csdn.net/tangbin330/article/details/8742600https://blog.csdn.net/tangbin330/article/details/8742600tangbin330Sun, 31 Mar 2013 13:05:17 +0800https://blog.csdn.net/tangbin330/article/details/8717258https://blog.csdn.net/tangbin330/article/details/8717258tangbin330Mon, 25 Mar 2013 15:27:03 +0800https://blog.csdn.net/tangbin330/article/details/8716060https://blog.csdn.net/tangbin330/article/details/8716060tangbin330Mon, 25 Mar 2013 11:15:06 +0800