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:
on my knowledge i can tell you the methods used to solve it which are;
Step-by-step explanation:
<h3>Elimination method.</h3><h3>Substitution method.</h3><h3>Graphical method.</h3>
Answer:
Step-by-step explanation:
percent increase = increase divided by original number x 100
increase is the difference between the two numbers...
new number - original number.....4000 - 2800 = 1200
percent increase = (1200 / 2800) x 100
= 0.42857 (round to .4286) x 100
= 42.86 %.....if you need it rounded to the nearest percent, it would be 43% increase
There 8 more orders of Pepsi then Mountain dew.
Answer:
D
Step-by-step explanation: