What is the Generalization of the Chi-square Distribution?

In summary, a Chi square distribution is a type of probability distribution used for analyzing categorical data. It is different from a normal distribution in terms of shape and the type of data it is used for. The formula for calculating a Chi square distribution involves the observed and expected frequencies. It is typically used in genetics, social sciences, and market research. To interpret the results of a Chi square test, the calculated value is compared to the critical value, and if it is greater, there is a significant difference between the observed and expected frequencies.
  • #1
EngWiPy
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What is the Multinomial expansion of the CDF of the Chi-square distribution?
Thanks in advance
 
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  • #2
Multinomial is generalized form of binomial.
First step of generalization of chi sq is Non Central Chi sq.
 

Related to What is the Generalization of the Chi-square Distribution?

What is a Chi square distribution?

A Chi square distribution is a probability distribution that is used to analyze categorical data. It is a type of continuous probability distribution that is used to determine the likelihood of observing a certain number of events or outcomes within a given sample size.

How is a Chi square distribution different from a normal distribution?

A Chi square distribution is different from a normal distribution in several ways. First, a Chi square distribution is a right-skewed distribution, while a normal distribution is a symmetrical bell-shaped curve. Additionally, a Chi square distribution is only used for categorical data, while a normal distribution is used for continuous data.

What is the formula for calculating a Chi square distribution?

The formula for calculating a Chi square distribution is: χ² = Σ (O - E)² / E, where χ² is the Chi square statistic, O is the observed frequency, and E is the expected frequency.

In what situations is a Chi square distribution typically used?

A Chi square distribution is typically used in situations where the researcher is interested in analyzing categorical data and determining if there is a significant difference between observed and expected frequencies. It is commonly used in genetics, social sciences, and market research.

How do I interpret the results of a Chi square test?

To interpret the results of a Chi square test, you must first calculate the Chi square statistic using the formula mentioned earlier. Then, you can compare the calculated value to the critical value from a Chi square table. If the calculated value is greater than the critical value, then there is a significant difference between the observed and expected frequencies. This indicates that the results are not due to chance and there is a relationship between the variables being studied.

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