Type II Error:
In a test of significance, Type II error is the error of accepting the null hypothesis when it is false — of failing to declare a real difference as statistically significant. Obviously, the bigger your samples, the more likely your test is to detect any difference that exists. The probability of detecting a real difference of specified size (i.e. of not committing a Type II error) is called the power of the test.
Planning on taking an introductory statistics course, but not sure if you need to start at the beginning? Review the course description for each of our introductory statistics courses and estimate which best matches your level, then take the self test for that course. If you get all or almost all the questions correct, move on and take the next test.
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