ࡱ> KMJ'` 2bjbj 4:6 ````,T!|(!*!*!*!*!*!*!$a#h%N!QN!!(!(! V2`. !0!&&&& l"N!N! ! \ \ Chi Square Statistical Analysis of Onion Root Tip Mitosis Today, we will be using statistics to test hypotheses, through the Chi Square Test. This test compares actual (observed) and predicted (expected) outcomes of an experiment. For each type of outcome (in our case, the phases in mitosis) in the experiment, there are both observed and expected numbers of occurrences. The Chi square statistic is used in this test:. Statisticians have determined the probability distribution of the Chi square statistic. You will use Table 1 for the Chi square statistic to analyze your results. This table will let you decide if the difference between observed and expected values is small enough to be due to chance (meaning the hypothesis may be true) or is too large to be due to chance (meaning the hypothesis produces a poor prediction of your results and is unlikely to be true). The equation for Chi Square Statistics: X2= (o-e)2/e o=observed e=expected Table 1. Chi Square Probability Table Degree of Freedom (df)Critical Value for p value of 0.0513.84125.99137.81549.488511.07 (P value is the probability that the deviation of the observed from that expected is due to chance alone (no other forces acting). In this case, using p > 0.05, you would expect any deviation to be due to chance alone 5% of the time or less. Degrees of freedom= k-1 k= #of categories Interpreting Your Results If the p value is greater than the Chi Square value calculated, accept the null hypothesis which states that differences that do exists are a result of random differences that arise from drawing a random sample. Reject alternate hypothesis that other factors are involved. If the p value is less than the Chi Square value calculated, reject the null hypothesis and accept the alternate hypothesis that some of factor is involved accounting for the deviation being so great. Directions: Use the pictures sent to your Google account to figure out the p value for the 3 onion root tip slides. We expec(rtv  0 2 , . 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