If a test is done with a 95% confidence interval, what would be the percentage of Type 1 error? could you explain the theory behind the answer as well that would be appreciated.
2026-03-27 07:28:14.1774596494
Hypothesis testing Type 1/2 error
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1
You could read the definitions of Type 1 error and confidence interval. They are not comparable without further information. Saying a test is done with a $95\%$ confidence interval says there is that chance the true value is within the quoted range. A Type 1 error says you reject the null hypothesis incorrectly. You have not specified how the result of the test causes you to reject the null hypothesis. I suspect the basis of the question is that the null hypothesis is a specific value of some parameter. Now you measure that parameter and disagree with that specific value at the $95\%$ confidence level. Your value is presumably some distance from the specific value, but your test assigns some probability to the case the true value is even farther from the specific value.