Answer:
Type I: 1.9%, Type II: 1.6%
Step-by-step explanation:
given null hypothesis
H0=the individual has not taken steroids.
type 1 error-falsely rejecting the null hypothesis
⇒ actually the null hypothesis is true⇒the individual has not taken steroids.
but we rejected it ⇒our prediction is the individual has taken steroids.
typr II error- not rejecting null hypothesis when it has to be rejected
⇒actually null hypothesis is false ⇒the individual has taken steroids.
but we didnt reject⇒the individual has not taken steroids.
let us denote
the individual has taken steroids by 1
the individual has not taken steroids.by 0
predicted
1 0
actual 1 98.4% 1.6%
0 1.9% 98.1%
so for type 1 error
actual-0
predicted-1
therefore from above table we can see that probability of Type I error is 1.9%=0.019
so for type II error
actual-1
predicted-0
therefore from above table we can see that probability of Type I error is 1.6%=0.016
Answer:
3m^2
Step-by-step explanation:
i hope this helps!! :)
Answer: 1/2
When looking at a graph, you need to follow the formula rise/run. This means that between two points, you need to find the distance up and down/left and right.
Looking at points (0,2) and (2,3), I see that the second point is 1 point higher. Let’s add that in for rise.
Rise/run
1/run
Now for run. The second point is 2 points to the right of the first one. Let’s add that in.
1/2
This is your answer! Hope this helps comment below for more questions :)
Answer:
$2.92
Step-by-step explanation:
35/12 = 2.91666666667
1 rose = 2.91666666667 = $2.92
The company should predict about 125 packages will have incorrect weights.
