The Chi-Squared Test demonstrates the **liklihood that data sets may be different from the expectation due to chance**.

It is therefore important to be able to describe what the result of the test means.

The **null hypothesis** normally assumes that there is no difference in the data (meaning that there *isn't* a reason for any differences, and they are down to chance).

If the *critical value *(normally *p=0.05* for Biology) is less than the **x**^{2 }then the test has been passed: the differences in data *aren't due to chance. There is a reason for* them.* *The null hypothesis can be rejected.

If the *critical value* is more than the **x**^{2 }then the test has been failed; the differences in data *are likely due to chance. There may not be a known reason for* them. The null hypothesis can be accepted.

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