state the possible type I and type ll errors
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In statistics, a Type I error means rejecting the null hypothesis when it's actually true, while a Type II error means failing to reject the null hypothesis when it's actually false. ... This means that your results only have a 5% chance of occurring, or less, if the null hypothesis is actually true.
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