Answer:
It is not a Type I error neither a Type II error.
Step-by-step explanation:
Let 
be the true mean match score. The null hypothesis is 
and the alternative hypothesis is 
(upper-tail alternative). When the test shows that the mean match score is more than 80 when actually is equal to 80 a Type I error is made. On the other hand, when the test shows that the mean match score is equal to 80 when actually is more than 80 a type II error is made. Therefore, when the test shows that the mean match score is more than 80 when the person does not actually have a fingerprint match, does not correspond to a Type I error neither to a Type II error.
Answer:
what
Step-by-step explanation:
1) Solving in terms of h
V = lwh <em>Divide both sides by h</em>
<em />
So rearranging that equation we can find h, in terms of V, and l and w.
If we want to solve in terms of l, or w, we'll proceed similarly to isolate the variable we want on the left side, and the other terms on the right side.
As x increases, y increases. So this data has a positive association. The association looks to be strong, as the values all follow the trend pretty closely.
Answer=Strong Positive
