Hypothesis Test for Balanced Load on 6 I/O Channels - N = 150

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In summary, the conversation discusses using the chi square test to test the hypothesis that the load on 6 I/O channels is balanced. The test uses the formula \chi^2=\sum (O-E)^2/E and E is calculated as \Sigma x_i/6, where x_i is the number of operations directed to each channel. The person asking for confirmation mentions that if each operation is equally probable, E should be 25.
  • #1
TomJerry
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Question : A computer system has 6 I/O channels and the system personnel are reasonably certain that the load on channels is balanced. If X is random variable denoting the index of the channel to which a given I/O operations is directed , that its pmf is assumed to be uniformly distributed. Out of N=150 I/O operation onserved, the number of operations directed to various channels were:
n0 = 22 ; n1 = 23 ; n2 = 29 ; n3 = 31 ; n4 = 26 ; n5 = 19

Test the hypothesis that the load on channels is balanced at 5 percent level of significance.

Solution
I have used the [tex]\chi[/tex]2 = (O-E)2 / E

where O - obsevred and E is expected

Is this correct or should i be using some other method
 
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  • #2
TomJerry said:
Question :

where O - obsevred and E is expected

Is this correct or should i be using some other method

You can use the chi square test [tex]\chi^2=\sum (O-E)^2/E[/tex] Do you know how to get E?
 
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  • #3
SW VandeCarr said:
You can use the chi square test [tex]\chi^2=\sum (O-E)^2/E[/tex] Do you know how to get E?

I have taken all the E = [tex]\Sigma[/tex]xi/6

Is that correct?
 
  • #4
TomJerry said:
I have taken all the E = [tex]\Sigma[/tex]xi/6

Is that correct?

Yes. If each I/O is taken as equally probable, 150/6=25=E.
 
  • #5
SW VandeCarr said:
Yes. If each I/O is taken as equally probable, 150/6=25=E.

Thanks
 
  • #6
If you're being sarcastic, why did you ask for confirmation in the first place?
 
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What is a hypothesis test?

A hypothesis test is a statistical method used to determine if there is enough evidence to reject or accept a proposed hypothesis about a population. It involves collecting and analyzing data to make an inference about the population.

Why is a hypothesis test important?

A hypothesis test is important because it allows scientists to make informed decisions about their research. By using statistical methods to analyze data, scientists can determine if their hypothesis is supported by the evidence or if it should be rejected.

What are the steps involved in a hypothesis test?

The steps involved in a hypothesis test include: stating the null and alternative hypothesis, selecting a significance level, choosing an appropriate statistical test, collecting and analyzing data, and making a decision based on the results.

What is a null hypothesis?

A null hypothesis is a statement that assumes there is no significant difference between the observed data and the expected results. It is the default assumption and is typically denoted as H0.

How do you interpret the results of a hypothesis test?

The interpretation of the results of a hypothesis test depends on the significance level chosen and the p-value calculated. If the p-value is less than the significance level, the null hypothesis is rejected, and there is enough evidence to support the alternative hypothesis. If the p-value is greater than the significance level, then the null hypothesis is not rejected, and there is not enough evidence to support the alternative hypothesis.

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