This is a special case of the gamma distribution
This can be used to calculate confidence interval estimates for population variances and standard deiations na din testing hypothesis involving the same parameters.
This type of distribution is also relevant when testing for goodness of fit, homogeneity and independence
Products and Squares of approximately normal distributed tend to have chi-squared distributions
This type of distribution consists of a whole family distinguised by a single whole number parameter v, called the number of degress of freedom
mean = v
variance = 2v
Has a family specified by the degrees of freedom "v"
Probability Distribution Graph
For values of v larger than 30 this type of distribution can be well approximated as a normal distribution.
Cumulative Distribution Graph
Returns the probability of getting "less than" or "equal to" a specific random variable x
CHISQ.DIST - (left tail) The cumulative beta probability density function
Returns the random variable where the probability of getting less than it is P.
CHISQ.INV - (left tail) The inverse
CHISQ.DIST.RT - (2010 - CHIDIST) (right tail)
CHITEST(observed freq range, expected freq range) - return p-value for testing observed versus expected frequencies. Does not compute expected frequencies
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