Difference between revisions of "Hypothesis Testing"


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<center>H. Kemal Ilter<br>2020</center>
 
<center>H. Kemal Ilter<br>2020</center>
  
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==Concepts==
  
 
# The ''null hypothesis'' {{#tag:math|H_0}} is a claim about the value of a population parameter. The ''alternate hypothesis'' {{#tag:math|H_1}} is a claim opposite to {{#tag:math|H_0}}.
 
# The ''null hypothesis'' {{#tag:math|H_0}} is a claim about the value of a population parameter. The ''alternate hypothesis'' {{#tag:math|H_1}} is a claim opposite to {{#tag:math|H_0}}.
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# A ''rejection region'' is the set of all values of a test statistic for which {{#tag:math|H_0}} is rejected.
 
# A ''rejection region'' is the set of all values of a test statistic for which {{#tag:math|H_0}} is rejected.
 
# ''Type I error'': you reject {{#tag:math|H_0}} when {{#tag:math|H_0}} is true. {{#tag:math|P(\text{Type I error}) = P(\text{reject }H_0 \mid H_0\text{ true}) = \alpha}}. The resulting {{#tag:math|\alpha}} is called the significance level of the test and the corresponding test is called a level {{#tag:math|\alpha}} test. We will use test procedures that give {{#tag:math|\alpha}} less than a specified level (0.05 or 0.01).
 
# ''Type I error'': you reject {{#tag:math|H_0}} when {{#tag:math|H_0}} is true. {{#tag:math|P(\text{Type I error}) = P(\text{reject }H_0 \mid H_0\text{ true}) = \alpha}}. The resulting {{#tag:math|\alpha}} is called the significance level of the test and the corresponding test is called a level {{#tag:math|\alpha}} test. We will use test procedures that give {{#tag:math|\alpha}} less than a specified level (0.05 or 0.01).
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==A Problem==
  
 
{{References}}
 
{{References}}
 
[[Category:Blog]]
 
[[Category:Blog]]

Revision as of 08:34, 16 November 2020

H. Kemal Ilter
2020


Concepts

  1. The null hypothesis [math]H_0[/math] is a claim about the value of a population parameter. The alternate hypothesis [math]H_1[/math] is a claim opposite to [math]H_0[/math].
  2. A test of hypothesis is a method for using sample data to decide whether to reject [math]H_0[/math]. [math]H_0[/math] will be assumed to be true until the sample evidence suggest otherwise.
  3. A test statistic is a function of the sample data on which the decision is to be based.
  4. A rejection region is the set of all values of a test statistic for which [math]H_0[/math] is rejected.
  5. Type I error: you reject [math]H_0[/math] when [math]H_0[/math] is true. [math]P(\text{Type I error}) = P(\text{reject }H_0 \mid H_0\text{ true}) = \alpha[/math]. The resulting [math]\alpha[/math] is called the significance level of the test and the corresponding test is called a level [math]\alpha[/math] test. We will use test procedures that give [math]\alpha[/math] less than a specified level (0.05 or 0.01).

A Problem



References