In an attempt to reduce the likelihood of a type ii error, the experimenter proposes to recruit a very large group of participants.
In statistical hypothesis testing, a Type I error is actually an incorrect rejection of the true null hypothesis (a.k.a. a "false positive" result or conclusion; e.g., "Innocent person convicted ing"). Rejection of one actually false null hypothesis (also called a "false negative" result or conclusion, e.g. "guilty party not convicted").
Many statistical theories revolve around minimizing one or both of these errors, but unless the outcome is determined by a known and observable causal process, either of these errors can be completely quantified. It is statistically impossible to eliminate You can improve the quality of the hypothesis test by choosing a lower threshold (cutoff) and changing the alpha (α) level. Knowledge of type I and type II errors is widely used in medicine, biometrics, and computer science.
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I believe the answer is: all three - age, class, and our place in history - because those are all ways in which society guides college attendance
In almost all societies, we have age requirement before we can fill out college application. Our palce in history is strongly correlated to the type of class that can enter college. In the past, only people with strong nobility background have the right to enter college, nowdays all classess of citizens have the right to enter college.
The answer is C
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if you run a business on your property in a separate structure, it is generally not covered by homeowners insurance.
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