pg 90 Chi Squared

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Chi Square (Χ²) Modeling using Candy

The Chi Square test is often used in science to determine if data you observe from an experiment is close enough to the predicted data.  In genetics, for instance, you might expect to get a 3:1 ratio if you crossed two heterozygous tall plants (Tt x Tt).  Calculating the Χ² values help you determine whether the results follow the prediction and if the variations from the exact ratio are due to random chance.  It’s the question of “how close is close enough?” If the numbers differ greatly from your expected results, then it’s possible that other factors may be influencing your results.

A chi square analysis requires a scientist to propose a null hypothesis and an alternative hypothesis.  IN statistics, the only way of supporting your hypothesis is to refute the null hypothesis.  IN other words, rather than trying to prove your idea right, you must show that the other idea (hypothesis)is likely to be wrong.  That is your NULL hypothesis.

Chi square values are used to show that the likelihood that the outcome is due to random chance is very unlikely.  An alternative hypothesis can never be proven, data can only reject or fail to reject the null hypothesis.

 



adapted from biologycorner.com