Statistics 简明教程

Statistics - Hypothesis testing

统计假设是关于总体的一个假设,该假设可能为真也可能为假。假设检验是统计学家用来接受或拒绝统计假设的一组正式程序。统计假设分为两种类型:

A statistical hypothesis is an assumption about a population which may or may not be true. Hypothesis testing is a set of formal procedures used by statisticians to either accept or reject statistical hypotheses. Statistical hypotheses are of two types:

  1. *Null hypothesis, ${H_0}$ * - represents a hypothesis of chance basis.

  2. *Alternative hypothesis, ${H_a}$ * - represents a hypothesis of observations which are influenced by some non-random cause.

Example

假设我们想要检查一枚硬币是否是公平且均衡的。零假设可能说,一半的正面和一半的背面,而备择假设可能说,正面的翻转和反面的翻转可能非常不同。

suppose we wanted to check whether a coin was fair and balanced. A null hypothesis might say, that half flips will be of head and half will of tails whereas alternative hypothesis might say that flips of head and tail may be very different.

例如,如果我们抛硬币 50 次,其中出现 40 次正面和 10 次反面。使用结果,我们需要拒绝零假设,并根据证据得出结论,该硬币可能不公平且不均衡。

For example if we flipped the coin 50 times, in which 40 Heads and 10 Tails results. Using result, we need to reject the null hypothesis and would conclude, based on the evidence, that the coin was probably not fair and balanced.

Hypothesis Tests

统计学家使用以下正式流程来确定是否根据样本数据拒绝零假设。此过程称为假设检验,并包含以下四个步骤:

Following formal process is used by statistican to determine whether to reject a null hypothesis, based on sample data. This process is called hypothesis testing and is consists of following four steps: