Calculating P-value from the chi-square test?

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Calculating the P-value from a chi-square test involves integrating over the relevant range of the probability density function. While some participants suggest using computer software or online calculators for convenience, others express a desire to perform the calculation manually. A specific resource was shared, directing users to an online chi-square demo for further assistance. The discussion highlights the balance between manual calculation and the ease of using digital tools. Ultimately, understanding the integration process is crucial for accurate P-value determination in chi-square tests.
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How do we calculate the P-value from the chi-square test? Is their some formula for doing so? I want to do it by hand and not by some online calculator or application.
 
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You integrate over the relevant range of the probability density function.
 
Following Number Nine's advice use a computer software package or look on the internet for an actual calculator. Google returns:

http://www.stat.tamu.edu/~west/applets/chisqdemo.html
 
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Thread 'Hypothesis testing: Defining H0, HA hypotheses so that ( H_A)_A' makes sense'

The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...
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