What are significance levels in statistics?
An example of an AI chatbot conversation about significance levels in statistics.
What are significance levels in statistics?
Significance levels, often denoted as alpha (α), are thresholds used to determine whether to reject the null hypothesis in hypothesis testing.
How do you choose a significance level?
Typically, a significance level of 0.05 is used, but it can vary based on the field of study or specific research requirements.
What does a significance level of 0.01 mean?
A significance level of 0.01 indicates a 1% risk of concluding that a difference exists when there is no actual difference.
Can you explain Type I and Type II errors?
Sure! A Type I error occurs when you reject a true null hypothesis, while a Type II error happens when you fail to reject a false null hypothesis.
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