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What is a Type I error

What is a Type I error - What is a Type I error Explain how...

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What is a Type I error? Explain how the cumulative Type I error affects your decision making . How are the two independent sample t-tests different from ANOVA? Type I error (the false positive ) is the error of rejecting the null hypothesis when it is actually true (For example, as in a student accused of copying in an examination when she really did not) Cumulative Type I Error is a Type I error whose magnitude does not approach zero as the number of observations increases. For alpha = 0.01, the accumulative error = 1 - 0.99^n (when the same outcome is evaluated n times). The Cumulative Type I error increases as n increases. With high cumulative Type I error, the null hypotheses may, in the long run, be rejected more frequently. ANOVA and two-sample t- test are similar in the sense that they are both meant to perform the same task - to test if two (or more) samples come from the same population or from different populations. That is, both the tests are employed to check if at least one of all the different samples taken has a mean which is different from those of the rest.

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