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# How to Read Chi Square Table?

TopChi – square table or chi – squared is used for purpose of solving problems related to Probability theory and statistical concept. With “n” degrees of freedom it is a method for distribution of a summation of the squares of “n” self - determining standard random variables. Chi - square is a collection of three features namely: size of Standard Deviation, size of Set or sample and number of clusters we have considered. It is very useful in assumption testing or in building confidence intervals and so it is one of the most widely used Probability Distribution techniques in stats. Chi – square is larger for larger deviations or larger groups. This distribution is also called as the central chi - square distribution. Let us know how to read chi Square table.
There are several possible situations where chi – square distribution table can be used like checking truthfulness of observed value against theoretical one, checking for in- dependency of two standards of classification of qualitative subject, and in estimation of confidence intervals also we can use this distribution method for a value of standard deviation of a normal probability distribution from a given standard deviation.
Definition of chi – square table can be given as follows:
Suppose we have X1, X2, X3, X4 …………… Xn as our standard normal random variables with independent nature. Their summation of squares can be evaluated as follows:
Sum = sum (i = 1k X_ (i2) is distributed according to chi - square distribution table having “n” degrees of freedom. This is typically represented as:
Q sum chi2 (k) text or Q sum chi2 _k.
In general, if chi - square value is greater, standard deviations are more probable to be noteworthy, and data is less probable to satisfy our expectations.