04
Dec
Chi Square Statistic Formula. The formula for the chi-square statistic used in the chi-square test is. Is a fancy symbol that means sum O. The Chi-square formula is used in the Chi-square test to compare two statistical data sets. The data used in calculating a chi-square statistic must be random raw mutually exclusive drawn.
A chi square distribution with n degrees of freedom is equal to a gamma distribution with a n 2 and b 05 or β 2. For example tossing a coin more than one hundred times represents a chi-square χ2 statistic because the null hypothesis of the chi-square test is that the coin has equal chances of landing on the tail or head every time it is tossed. For this we need to compare the value with the critical value of the distribution with the corresponding degrees of freedom. Divide every one of the squared difference by the corresponding expected count. P -value CHIDIST xdegree_of_freedom Put in the values and this will give you a p-value for the given data points mentioned above. We use the following formula to calculate the Chi-Square test statistic X2.
Next we have to take a decision whether it is statistically significant or not.
The data used in calculating a chi-square statistic must be random raw mutually exclusive drawn. Divide every one of the squared difference by the corresponding expected count. The rest of the calculation is difficult so either look it up in a table or use the Chi-Square Calculator. The subscript c here are the degrees of freedom. Σ means to sum up see Sigma Notation O each Observed actual value. If the p-value that corresponds to the test statistic X2 with rows-1 columns-1 degrees of freedom is less than your chosen significance level then you can reject the null hypothesis.