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<!DOCTYPE html>
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<h1>看见统计</h1>
<p >看得见的统计概率入门</p>
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<li class="active" id='submenu-bp'><a href="#secondPage/chapter1">基础概率论</a></li>
<li id='submenu-cp'><a href="#secondPage/chapter2">进阶概率论</a></li>
<li id='submenu-pd'><a href="#secondPage/chapter3">概率分布</a> </li>
<li id='submenu-fi'><a href="#secondPage/chapter4">统计推断:频率学派</a> </li>
<li id='submenu-bi'><a href="#secondPage/chapter5">统计推断:贝叶斯学派</a> </li>
<li id='submenu-ra'><a href="#secondPage/chapter6">回归分析</a> </li>
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<div class="slide" id="chapter1" data-anchor="chapter1">
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<h4>第一章</h4>
<h1>基础概率论</h1>
<p>本章主要介绍了概率论中的一些基本概念</p>
</br>
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<a href="./basic-probability/cn.html">
<div id="bp" class='rec_button'>进入 基础概率论</div>
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<div class="nav-unit-wrapper-s tile1">
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<span class="nav-unit-title-s"> 随机事件 </span>
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<span class="nav-unit-title-s">  方差  </span>
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<h4>第二章</h4>
<h1>进阶概率论</h1>
<p>本章进一步介绍了概率论中的一些核心知识</p>
</br>
</br>
<a href="./compound-probability/cn.html">
<div id="cp" class='rec_button'>进入 进阶概率论</div>
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<div class="nav-unit-wrapper-s tile1">
<img src="img/tiles/2-1.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 集合论 </span>
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<div class="nav-unit-wrapper-s tile2">
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<span class="nav-unit-title-s"> 古典概型 </span>
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<div class="nav-unit-wrapper-s tile3">
<img src="img/tiles/2-3.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 条件概率</span>
</div>
</a>
</div>
</div>
</div>
</div>
<div class="slide " id="chapter3" data-anchor="chapter3">
<div class="chapter-nav">
<div class="left">
<h4>第三章</h4>
<h1>概率分布</h1>
<p>概率分布描述了所有可能出现的事件的概率</p>
</br>
</br>
<a href="./probability-distributions/cn.html">
<div id="pd" class='rec_button'>进入 概率分布</div>
</a>
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<a href="./probability-distributions/cn.html#section1">
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<img src="img/tiles/3-1.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 随机变量 </span>
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<div class="nav-unit-wrapper-s tile2">
<img src="img/tiles/3-2.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 离散型和连续型随机变量</span>
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<span class="nav-unit-title-s"> 中心极限定理 </span>
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<div class="chapter-nav">
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<h4>第四章</h4>
<h1>统计推断:频率学派</h1>
<p>频率学派的思想是用观察到的数据来确定背后的概率分布。</p>
</br>
</br>
<a href="./frequentist-inference/cn.html">
<div id="fi" class='rec_button'>进入 统计推断:频率学派</div>
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<img src="img/tiles/4-1.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 点估计理论 </span>
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<div class="nav-unit-wrapper-s tile2">
<img src="img/tiles/4-2.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 置信区间 </span>
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<span class="nav-unit-title-s"> Bootstrap方法</span>
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</div>
</div>
</div>
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<div class="chapter-nav">
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<h4>第五章</h4>
<h1>统计推断:贝叶斯学派</h1>
<p>贝叶斯学派的思想是用数据来更新特定假设的概率。</p>
</br>
</br>
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<div id="bi" class='rec_button'>进入统计推断:贝叶斯学派</div>
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<div>
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<div class="nav-unit-wrapper-s tile1">
<img src="img/tiles/5-1.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 贝叶斯公式</span>
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</a>
<a href="./bayesian-inference/cn.html#section2">
<div class="nav-unit-wrapper-s tile2">
<img src="img/tiles/5-2.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 似然函数 </span>
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<div class="nav-unit-wrapper-s tile3">
<img src="img/tiles/5-3.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 从先验概率到后验概率 </span>
</div>
</a>
</div>
</div>
</div>
</div>
<div class="slide" id="chapter6" data-anchor="chapter6">
<div class="chapter-nav">
<div class="left">
<h4>第六章</h4>
<h1>回归分析</h1>
<p>回归分析是一种建立两个变量之间线性模型的方法</p>
</br>
</br>
<a href="./regression-analysis/cn.html">
<div id="ra" class='rec_button'>进入 回归分析</div>
</a>
</div>
<div class="right">
<div>
<a href="./regression-analysis/cn.html#section1">
<div class="nav-unit-wrapper-s tile1">
<img src="img/tiles/6-1.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 最小二乘法 </span>
</div>
</a>
<a href="./regression-analysis/cn.html#section2">
<div class="nav-unit-wrapper-s tile2">
<img src="img/tiles/6-2.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 相关性 </span>
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<a href="./regression-analysis/cn.html#section3">
<div class="nav-unit-wrapper-s tile3">
<img src="img/tiles/6-3.png" class="nav-unit-tile-s">
<span class="nav-unit-title-s"> 方差分析 </span>
</div>
</a>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="section" id="section2">
<div class="section-wrapper">
<div class="about">
<P>
看见统计由Daniel Kunin在布朗大学读本科的时候开始制作。我们致力于用数据可视化让统计概念更容易理解。 (数据可视化使用Mike Bostock的javascript库<a href="https://d3js.org/" style="color:#64bdff; text-decoration: underline;">D3.js</a>制作。)</br>
</P>
</br>
<p>团队</p>
<div class="team">
<a href="http://daniel-kunin.com/">
<img src="img/team/daniel.png">
<p>Daniel</br> Kunin</p>
</a>
</div>
<div class="team">
<a href="http://www.jingru-guo.com">
<img src="img/team/jingru.png">
<p>Jingru</br> Guo</p>
</a>
</div>
<div class="team">
<a href="https://www.linkedin.com/in/tyler-dae-devlin/">
<img src="img/team/tyler.png">
<p>Tyler</br> Dae Devlin</p>
</a>
</div>
<div class="team">
<a href="https://math.stackexchange.com/users/303759/daniel-xiang">
<img src="img/team/dan-xiang.jpg">
<p>Daniel</br> Xiang</p>
</a>
</div>
<div class="team">
<a href="https://profiles.stanford.edu/zhimei-ren?releaseVersion=7.5.0">
<img src="img/team/zhimei.png">
<p>Zhimei</br> Ren</p>
</a>
</div>
<p>奖项&媒体</p>
<a href="https://www.informationisbeautifulawards.com/showcase/2296-seeing-theory">
<img src="img/award/iib.svg" class='award'>
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</a>
<a href="https://www.fastcodesign.com/3068795/a-visual-guide-to-statistics">
<img src="img/award/fastco.svg" class='award'>
</a>
<a href="http://capeandislands.org/post/websites-will-make-you-fall-love-statistics#stream/0">
<img src="img/award/wcai.svg" class='award'>
</a>
<a href="https://thenextweb.com/apps/2017/03/01/interactive-webiste-statistics-boring/">
<img src="img/award/tnw.svg" class='award'>
</a>
<a href="https://www.sxsw.com/awards/interactive-innovation-awards/">
<img src="img/award/sxsw.svg" class='award'>
</a>
<a href="http://www.browndailyherald.com/2018/02/08/brown-risd-grads-craft-online-statistics-resource/">
<img src="img/award/bdh.png" class='award'>
</a>
<a href="https://www.webbyawards.com/winners/2018/websites/general/education/seeing-theory/">
<img src="img/award/webby.png" class='award'>
</a>
</div>
</div>
</div>
<div class="section" id="section3">
<div class="section-wrapper">
<div class="buy-book">
<p>
我们正在把Seeing Theory的内容集结成书,欢迎点击下方链接下载最新的英语版本。欢迎向我们提供<a href="http://seeingtheory.civicomment.org/seeing-theory-notes" style="color:#64bdff; text-decoration: underline;">反馈</a>。
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<h6>打赏</h6>
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