Chi Square:
We learned about this concept called Chi
square test which is basically used in order to compare an observed data with
the expected data in the example of Subset where we found out whether there was
a relationship between different variables e.g. relationship between races and
the age when person got first married.
We can find this by preparing a Null
hypothesis. Null hypothesis is a statement that we make which describes that
there is no relationship between the two variables taken.
Though we
calculated the Chi-square test in the software, the statistical formula for
calculating chi-square is:
(o-e)2/e
That is,
chi-square is the sum of the squared difference between observed (o) and
the expected (e) data, divided by the expected data in all possible
categories.
Following is the interpretation that we could make:
Greater differences between expected
and actual data produce a larger Chi-square value. The larger the Chi-square value, the greater
the probability that there really is a significant difference. So, we should accept the Null
hypothesis.
That means there is no relationship between the two variables. Also,
it is a general rule that the larger the number of cases, it is easier to
achieve significance. For e.g., getting 6 sixes out of 10 rolls of dice is
likely by chance, but that does not mean, we will get 60 sixes in 100 rolls.
Chi-square itself says nothing about the strength of a
relationship, only its significance.
links:
http://search.mywebsearch.com/mywebsearch/redirect.jhtml?searchfor=chi+square+explained&cb=ZQ&n=77cfb37c&ptnrS=ZQxdm004YYIN&qid=a6b159645f64f74850f56b6dc8d78c9&action=pick&ss=sub&pn=1&st=kwd&ptb=iKZMLEBNKlopyWOpc_FEQQ&pg=GGmain&ord=0&redirect=mPWsrdz9heamc8iHEhldEcgdjfjqpMajKYmz288FhTKMAB7zL2gQKAN1rlHfY5SGyzscM4zZaVMAZS5fF98EGQ%3D%3D&ct=AR&tpr=sbt, http://www.stattools.net/ChiSqTest_Exp.php, http://search.mywebsearch.com/mywebsearch/redirect.jhtml?searchfor=chi+square+explained&cb=ZQ&n=77cfb37c&ptnrS=ZQxdm004YYIN&qid=a6b159645f64f74850f56b6dc8d78c91&action=pick&ss=sub&pn=1&st=kwd&ptb=iKZMLEBNKlopyWOpc_FEQQ&pg=GGmain&ord=2&redirect=mPWsrdz9heamc8iHEhldEXsAo%2F6TxgUNkatLZcdD9dkSRf3hJEmu5oF33MwIRCuNoZFH6%2FIpv%2BolNxX2la550SNlmm6Qczd3YYFXgTayN2c%3D&ct=AR&tpr=sbt.
Good value add in terms of knowing how to calculate the chi square value. Well verbalised in your own words. Would have been even better if you had explained the difference between strength and significance of relationship.
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