Test Statistic in Chi-Square Test

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SUMMARY

The discussion centers on the derivation and understanding of the test statistic in the Chi-Square test, specifically under the null hypothesis. It is established that the Chi-Square distribution with k degrees of freedom is derived from the sum of squares of k standard normal distributions. Each bin's contribution to the test statistic is represented as (observed - expected)² / expected, which follows a Chi-Square distribution with 1 degree of freedom. The linear restriction that the sum of the "(observed - expected)" values equals zero results in k - 1 degrees of freedom.

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  • Basic concepts of observed vs. expected values in data analysis
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ych22
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Can anyone come up with an intuitive explanation or point me to a link that gives a derivation of the test statistic in chi-square test? I am having problems understanding why the particular test statistic is approximated by a Chi-Square random variable under the null hypothesis of the chi-square test. I cannot find any helpful literature online or in my textbooks too.

After all, the chi-square distribution with k degrees of freedom arises from the sum of squares of k standard normal distributions. This implies that for each bin, (observed-expected)^2 /expected ~ chi-square(1). Why?
 
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Prepare for the incredibly non-formal discussion:
You have one linear restriction: the sum of the "(observed - expected)" values is zero. You have k statistics, with 1 restriction, hence k - 1 degrees of freedom.
 

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