Calculating P-value from the chi-square test?

In summary, the P-value from a chi-square test is calculated by determining the chi-square statistic and finding the corresponding area under the curve. The significance level, or alpha, is set at 0.05 and a negative P-value is not possible. A small P-value indicates a statistically significant result and a high P-value suggests no significant relationship between variables.
  • #1
hivesaeed4
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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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  • #2
You integrate over the relevant range of the probability density function.
 
  • #3
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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Related to Calculating P-value from the chi-square test?

1. How do you calculate the P-value from a chi-square test?

To calculate the P-value from a chi-square test, you first need to determine the chi-square statistic by performing the chi-square test on your data. Then, you can use a chi-square distribution table or a statistical software to find the area under the curve that corresponds to your chi-square statistic. This area represents the P-value.

2. What is the significance level for a chi-square test?

The significance level, also known as alpha, is the threshold for determining if the P-value is small enough to reject the null hypothesis in a chi-square test. It is typically set at 0.05 or 5%, meaning that if the P-value is less than 0.05, the results are considered statistically significant and the null hypothesis can be rejected.

3. Can you have a negative P-value from a chi-square test?

No, a P-value cannot be negative. It represents the probability of obtaining a result equal to or more extreme than the observed result, assuming the null hypothesis is true. Therefore, it is always a positive value between 0 and 1.

4. What does a small P-value from a chi-square test indicate?

A small P-value (typically less than 0.05) suggests that the results of the chi-square test are statistically significant, and the null hypothesis can be rejected. This means that there is a low probability that the observed data is due to chance and there is likely a relationship between the variables being tested.

5. Can a high P-value from a chi-square test be interpreted as evidence of no relationship between variables?

Yes, a high P-value (typically greater than 0.05) suggests that the results of the chi-square test are not statistically significant, and the null hypothesis cannot be rejected. This means that there is a high probability that the observed data is due to chance and there is not enough evidence to conclude that there is a relationship between the variables being tested.

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