标签：E8% E5% 假设检验 E6% E7% 统计学 AE% E4%

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参数估计与假设检验的区别

参数估计与假设检验是统计推断的两个组成部分，都是利用样本信息对总体进行推断，但是角度不同。
参数估计是样本统计量估计总体参数的方法，总体参数在估计前是未知的。
假设检验是先对总体参数提出一个假设，后用样本信息去验证这个假设是否正确。
参数估计不知道总体的信息，也不进行假定，假设不知道总体，需要验证信息。

1.假设检验的基本思想和原理
2.假设检验的步骤
3.一个总体参数的检验
4.两个总体参数的检验
5.P值的计算与应用
6.用EXCEL进行检验

假设检验的基本问题

1.假设问题的提出
2.假设的表达式
3.两类错误
4.假设检验的流程
5.利用P值进行决策

什么是假设？
对总体参数的具体数值所做的陈述
-总体参数包括总体均值、比例、方差等
-分析之前必需陈述

什么是假设检验
1.先对总体的参数(或分布形式)提出某种假设，然后利用样本信息判断假设是否成立的过程
2.有参数检验和非参数检验
3.逻辑上运用反证法，统计上依据小概率原理

原假设
1.研究者想收集证据予以反对的假设
2.又称为"0假设"
3.总是有符号=,≤或≥
4.表示为H0​
H0​:\mu=某一数值
指定为符号=,≤或≥
例如 H0​:μ=10cm
一般情况下，记原假设为H0​所谓为零假设
备择假设
1.研究者想收集证据予以支持的假设
2.也称为研究假设
3.总是有符号 !=,≤或≥
4.表示为H1​
H1​:μ<某一数值，或μ>某一数值
例如：H1​:μ<10cm,或mu>10cm
原假设和备择假设是属于非此即彼的关系，一般来说，原假设是包含等于的
提出假设
1.原假设和备择假设是一个完备事件组，而且相互独立
在一项假设检验中，原假设和备择假设必有一个条件成立，而且只有一个成立
2.先确定备择假设，再确定原假设
3.等号=总是放在原假设上
4.因研究目的不同，对同一问题可能提出不同的假设(也可能得出不同的结论)
双侧检验和单侧检验
1.备择假设没有特定的方向性，并含有符号≠的假设检验，称为双侧检验或双尾检验
2.备择假设具有特定的方向性，并含有符号≤和\req的假设检验，称为单侧检验或单尾检验

• 备择假设的方向为<,称为左侧检验
• 备择假设的方向为>,称为右侧检验

双侧检验和单侧检验的假设形式

假设	双侧检验	单侧检验(左侧)	单侧检验(右侧)
原假设	H0​:μ=μ0​	H0​:μ≥μ0​	H0​:μ≤μ0​
备择假设	H1​:μ≠μ0​	H1​:μ<μ0​	H1​:μ>μ0​

假设检验中的两类错误

• 1.第I类错误(弃真错误)
• 原假设为真，拒绝原假设
  第I类错误的概率记为α,被称为显著性水平
  2.第II类错误(取伪错误)
• 原假设为假设时未拒绝原假设
• 第II类错误的概率记为β
  两类错误时此消彼长的关系，不可能同时达到平衡，需要有所取舍

影响beta错误的因素

• 1.总体参数的真值
• 随着假设的总体参数的减少而增大
  2.显著性水平α
  当α减少时增大
  3.总体标准差
  当α增大时增大
  4.样本容量n
  当n减少时增大

显著性水平α
1.是一个概率值
2.原假设为真时，拒绝原假设的概率被称为抽样分布的拒绝域
表示为α

• 常用的alpha有0.01,0.05,0.1
  由研究者提出

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标签：E8%,E5%,假设检验,E6%,E7%,统计学,AE%,E4%
来源： https://www.cnblogs.com/pandaboy1123/p/11082798.html

本站声明： 1. iCode9 技术分享网（下文简称本站）提供的所有内容，仅供技术学习、探讨和分享；
2. 关于本站的所有留言、评论、转载及引用，纯属内容发起人的个人观点，与本站观点和立场无关；
3. 关于本站的所有言论和文字，纯属内容发起人的个人观点，与本站观点和立场无关；
4. 本站文章均是网友提供，不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属；如您发现该文章侵犯了您的权益，可联系我们第一时间进行删除；
5. 本站为非盈利性的个人网站，所有内容不会用来进行牟利，也不会利用任何形式的广告来间接获益，纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。