Blank boxes are not included in the calculations but zeros are. If your chi-square calculated value is less than the chi-square critical value, then you 'fail to reject' your null hypothesis. Enter the sample data Row-wise, and then click the Calculate button for the test conclusion. Any deviations greater than this level would cause us to reject our hypothesis and assume something other than chance was at play. (See red circle on Fig 5.) If your chi-square calculated value is greater than the chi-square critical value, then you reject your null hypothesis. By convention biologists often use the 5.0% value (p<0.05) to determine if observed deviations are significant. This means that a chi-square value this large or larger (or differences between expected and observed numbers this great or greater) would occur simply by chance between 25% and 50% of the time.

In our example, the X 2 value of 1.2335 and degrees of freedom of 1 are associated with a P value of less than 0.50, but greater than 0.25 (Follow blue dotted line and arrows in Fig 5). This will tell us the probability that the deviations (between what we expected to see and what we actually saw) are due to chance alone and our hypothesis or model can be supported. The calculated value of X 2 from our results can be compared to the values in the table aligned with the specific degrees of freedom we have. In this case the degrees of freedom = 1 because we have 2 phenotype classes: resistant and susceptible.

Degrees of freedom is simply the number of classes that can vary independently minus one, (n-1). Statisticians calculate certain possibilities of occurrence (P values) for a X 2 value depending on degrees of freedom.

Hypothesis test calculator p value