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24 October, 20:11

8 You estimate a simple linear regression model using a sample of 25 observations and obtain the following results (estimated standard errors in parentheses below coefficient estimates) : y = 97.25 + 19.74 * x (3.86) (3.42) You want to test the following hypothesis: H0:  2 = 1, H1:  2 >12. If you choose to reject the null hypothesis based on these results, what is the probability you have committed a Type I error?

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  1. 24 October, 21:53
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    Step-by-step explanation:

    Hello!

    In statistics, a Type I error is the probability of rejecting the null Hypothesis (i. e. supporting the alternative Hypothesis) when this Hypothesis is true. This probability is also know as the significance level of the test, symbolized α. So whatever the level of significance is, that is the probability of commiting Type I error. The most common significance level are it's 1%, 5% or 10%.

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