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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 ttests 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 twosample 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
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This note was uploaded on 01/05/2012 for the course 101 melissa jo taught by Professor Acc101 during the Spring '11 term at Aarhus Universitet.
 Spring '11
 acc101

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