Figure A12

95% confidence interval for x.

908 APPENDIX A: A REVIEW OF SOME STATISTICAL CONCEPTS

true; this is called a type I error (thus, in the preceding example XX = 67 could have come from the population with a mean value of 69), or (2) we may not reject H0 when it is, in fact, false; this is called a type II error. Therefore, a hypothesis test does not establish the value of true i . It merely provides a means of deciding whether we may act as if i =

Type I and Type II Errors. Schematically, we have

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