Tuesday, November 18th, 2014
The Chi square compares the observed data with the Null Hypothesis.
Chi square test looks at single set of data and Null Hypothesis.
Expected = row X col total / grand total
χ2 = sum ((observed – expected) /Expected)2
χ2 and DF/degree of freedom gives the test statistic
A big difference between observed and expected results in a large test statistic (χ2) and so leads to a rejection of the Null Hypothesis (Ho)
The greater the value of the test statistic, the greater the evidence against the Null hypothesis -leads to a smaller p -value
“…The p-value is the area under the chi-square probability density function (pdf) curve to the right of the specified χ2 value…” http://www.di-mgt.com.au/chisquare-calculator.h
p value is the area to the right of the test statistic. The less the number (< 0.05) the more likely to reject the Null Hypothesis
Nice video explaining it all.
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