Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授。

PDF笔记下载(Academia.edu)

Summary

Bayes Theorem $$P(A_i|B)=\frac{P(B|A_i)\cdot P(A_i)}{\sum_{j}P(B|A_j)\cdot P(A_j)}$$ where $$P(B)=\sum_{j}P(B|A_j)\cdot P(A_j)$$

GRADED EXERCISE SET 2

PROBLEM 1

Cards are dealt from a well shuffled standard deck. Find the chance that:

1A the first card is not a heart

1B the 10th card is the ace of spades

1C the 10th card is the ace of spades, given that the 50th card is the ace of diamonds

1D the 32nd card is red, given that the 51st and 52nd cards are red

1E the 51st card is red, given that the 32nd and 52nd cards are red

Solution

1A) $$P(\text{first card is not heart})=1-P(\text{first card is heart})=1-\frac{13}{52}=\frac{3}{4}$$

1B) Each card is randomly drawn thus the chance of a specific card is equivalent: $$P(\text{10th is ace of spades})=\frac{1}{52}$$

1C) There are 51 cards except the given card ace of diamonds, thus $$P(\text{10th is ace of spades}\ |\ \text{50th is ace of diamonds})=\frac{1}{51}$$

1D) $$P(\text{32nd is red}\ |\ \text{51st and 52nd are red})=\frac{26-2}{52-2}=\frac{12}{25}$$

1E) $$P(\text{51st is red}\ |\ \text{32nd and 52nd are red})=\frac{26-2}{52-2}=\frac{12}{25}$$

PROBLEM 2

A person is selected at random from a population that has the following characteristics: 65% of the people are men; the others are women 12% of the men are smokers 7% of the women are smokers

2A Find (correct to four decimal places) the chance that the selected person is a non-smoker, given that the person is a man.

2B Find (correct to four decimal places) the chance that the selected person is a woman who smokes.

2C Find (correct to four decimal places) the chance that the selected person is a smoker.

2D Given that the selected person is a smoker, what is the chance that the person is a woman? Please give your answer correct to four decimal places.

2E Find (correct to four decimal places) the chance that the selected person is a man or a non-smoker.

Solution

2A) $$P(\text{non-smoker}\ |\ \text{man})=1-0.12=0.88$$

2B) $$P(\text{woman & smoker})=(1-0.65)\times0.07=0.0245$$

2C) $$P(\text{smoker})=P(\text{smoker & man})+P(\text{smoker & woman})$$ $$=0.65\times0.12+(1-0.65)\times0.07=0.1025$$

2D) $$P(\text{woman}\ |\ \text{smoker})=\frac{P(\text{woman & smoker})}{P(\text{smoker})}=\frac{0.35\times0.07}{0.1025}=0.2390244$$

2E) $$P(\text{man or non-smoker})=P(\text{man})+P(\text{non-smoker})-P(\text{man & non-smoker})$$ $$=0.65+(1-0.1025)-0.65\times0.88=0.9755$$

PROBLEM 3

I am with a group of five of my friends. A box contains 8 pieces each of milk chocolate, white chocolate, and dark chocolate. The box is passed around the six of us, with each person taking 4 pieces. Assume that each person chooses at random without replacement from the available pieces. I am the last person to whom the box is passed. Find the chance that I pick 4 dark chocolates.

Solution

It it no difference between "I" am the first and "I" am the last. $$P=\frac{C_{8}^{4}}{C_{24}^{4}}=\frac{35}{5313}=0.006587615$$ $C_{n}^{m}=\frac{n!}{m!\cdot(n-m)!}$ and its R function is $\text{choose(n, m)}$.

PROBLEM 4

An urn contains 10 white balls and 5 blue balls. Draws are made repeatedly from the urn as follows. On each draw, a ball is drawn and its color noted; then it is replaced in the urn along with 3 more balls of its color. For example, if you draw a white ball the first time, then you will put it back in the urn along with 3 more white balls. So you will end up with 13 white balls and 5 blue balls.

4A Find the chance that the first ball drawn is blue.

4B Find the chance that the second ball drawn is blue, given that the first ball drawn is blue.

4C Find the chance that the second ball drawn is blue.

4D Find the chance that the first ball drawn is blue, given that the second ball drawn is blue.

Solution

4A) $$P(\text{first is blue})=\frac{5}{10+5}=\frac{1}{3}$$

4B) If the first is blue then it would be 10 white balls and 8 blue balls before the second draw. Hence $$P(\text{second is blue}\ |\ \text{first is blue})=\frac{8}{10+8}=\frac{4}{9}$$

4C) $$P(\text{second is blue})=P(\text{second is blue & first is white})+P(\text{second is blue & first is blue})$$ $$=P(\text{first is white})\cdot P(\text{second is blue}\ |\ \text{first is white})$$ $$+P(\text{first is blue})\cdot P(\text{second is blue}\ |\ \text{first is blue})$$ $$=\frac{10}{15}\times\frac{5}{13+5}+\frac{5}{15}\times\frac{8}{10+8}=\frac{1}{3}$$

4D) $$P(\text{first is blue}\ |\ \text{second is blue})=\frac{P(\text{first & second are blue})}{P(\text{second is blue})}=\frac{\frac{5}{15}\times\frac{8}{10+8}}{\frac{1}{3}}=\frac{4}{9}$$

加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 1 The Two Fundamental Rules (1.5-1.6)的更多相关文章

  1. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 5 The accuracy of simple random samples

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  2. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 4 The Central Limit Theorem

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  3. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 3 The law of averages, and expected values

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  4. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 2 Random sampling with and without replacement

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  5. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Final

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  6. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Midterm

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  7. 加州大学伯克利分校Stat2.3x Inference 统计推断学习笔记: FINAL

    Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  8. 加州大学伯克利分校Stat2.3x Inference 统计推断学习笔记: Section 2 Testing Statistical Hypotheses

    Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  9. 加州大学伯克利分校Stat2.3x Inference 统计推断学习笔记: Section 1 Estimating unknown parameters

    Stat2.3x Inference(统计推断)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

随机推荐

  1. Apache CXF实现WebService发布和调用

    第一种方法:不用导入cxf jars 服务端: 1. 新建Web工程 2.新建接口和实现类.测试类 目录结构图如下: 接口代码: package com.cxf.spring.service; imp ...

  2. 调用天气Api实现天气查询

    上面是简单截图: 前台代码: @{ Layout = null; } <!DOCTYPE html> <html> <head> <meta name=&qu ...

  3. SWIFT--文档地址

    APPLE官方: https://developer.apple.com/library/prerelease/content/documentation/Swift/Conceptual/Swift ...

  4. Beta版本冲刺Day3

    会议讨论: 628:已经将原本写在jsp中的所有界面修饰代码转移到了css文件中,同时当页面跳转的时候也不会出现崩溃的现象,并且已经解决了上次无法连接数据库的问题.但是又遇到了一些新的小问题,希望明天 ...

  5. js 对象数组根据对象中的属性排序

    function createComparisonFunction(propertyName){ return function(object1,object2){ var value1 = obje ...

  6. 开发错误日记 12: Unsupported major.minor version 52.0

    开发错误日记 12: Unsupported major.minor version 52.0 在编译时出现如下错误: java.lang.UnsupportedClassVersionError: ...

  7. 选项卡js

    趁着公司不忙,抓紧充充电,开始可能会写的不好,但是每写一个都是一点进步,哈哈,加油 用js实现选项卡切换 1.获取元素 2.初始状态 3.通过循环清空元素状态 4.点击操作以及对应的内容切换 5.自定 ...

  8. 【转】Web前端浏览器兼容初探

    原文地址:http://blog.jobbole.com/38638/ 前言 浏览器兼容是前端开发人员必须掌握的一个技能,但是初入前端的同学或者其他后台web开发同学往往容易选择忽略,而形成两个极端: ...

  9. puppet的配置

    1时间问题 agent与master端务必要保持时间的一致性,最好使用ntp服务 检查ntp服务是否安装 [root@master-elk ~]# rpm -qa|grep ntp ntpdate-. ...

  10. 简单的cookie使用

    <html><head><script type="text/javascript">function getCookie(c_name){if ...