Wednesday 11 January 2012

Chi-Square Test


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.

1 comment:

  1. 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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