US123456
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SIGNIFICANCE LEVEL: p ≤ 0.05 (probability of chance factors affecting the results is 5% or less)

Type II error – very stringent significance level (p<0.05) leading to non-significant results when they wouldn’t be if a higher level was used. This is known as a false negative. The researcher wrongly accepts the null hypothesis.

Type I error – a very high/lenient significance level (p>0.05) leading to significant results when they shouldn’t be if a lower level was used. This is known as a false positive. The researcher wrongly rejects the null hypothesis.


Can someone give examples of a type I and II error. I know the 2 types but I don't understand them.
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Sandra4938
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Thanks for providing the help
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Noodlzzz
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Sandra4938
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US123456
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(Original post by Noodlzzz)
lool. i guess that part wasn't as hard to understand as i thought it would be. However i still dont understand the part about significance level.
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chazwomaq
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(Original post by US123456)
SIGNIFICANCE LEVEL: p ≤ 0.05 (probability of chance factors affecting the results is 5% or less)
This definition of a significance level is not correct. It is actually "the probability of rejecting the null hypothesis, given that the null hypothesis is true."
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