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Hypothesis Testing

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Hypothesis Testing

The main problems in statistical inference can be broadly classified into two areas:

 

  • The area of estimation of population parameters and setting up confidence intervals for them, ie., the area of point and interval estimation and
  • Tests of statistical hypothesis.

 

Definition:

A statistical hypothesis is some statement or assertion about a population or equivalently about the probability distribution characterizing a population, which we want to verify on the basis of the information available from the sample. If the statistical hypothesis specifies the population completely then it is termed a simple hypothesis otherwise it is called a composite statistical hypothesis.

 

For example: If X1,X2,...,Xn is a random sample of size n from a normal population with mean μ and variance σ2 then the hypothesis H0:μ=μ0σ2=σ02 is a simple hypothesis, whereas each of the following is the composite hypothesis:

 

  1. μ=μ0
  2. σ2=σ02
  3. μ<μ0,σ2=σ02
  4. μ>μ0,σ2=σ02
  5. μ=μ0,σ2<σ02
  6. μ=μ0,σ2>σ02
  7. μ<μ0,σ2>σ02

 

A hypothesis that doesn't specify completely 'r' parameter of a population is termed as a composite hypothesis with r degree of freedom.


Checkpoint

Which of the following is an example of a composite hypothesis?

Test of a Statistical Hypothesis

A test of statistical hypothesis is a two-action decision problem after the experimental sample values have been obtained the two actions being the acceptance or rejection of the hypothesis under consideration.

 

Null HypothesisH0

This can be thought of as the implied hypothesis. “Null” means “nothing.”  This hypothesis states that there is no difference between groups or no relationship between variables. The null hypothesis is a presumption of status quo or no change.


Alternative HypothesisHA 

This is also known as the claim. This hypothesis should state what you expect the data to show, based on your research on the topic. This is your answer to your research question.


Checkpoint

Select the correct hypothesis:

 

There is no difference in the salary of factory workers based on gender:   
Male factory workers have a higher salary than female factory workers.

 
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