This graph the answer to your problem.
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
For this case we have a direct variation of the form:
Where,
- <em>k: proportionality constant
</em>
We must find the value of k.
For this, we use the following data:
Therefore, replacing values we have:
Rewriting:
Clearing the value of k we have:
Therefore, the direct variation equation is given by:
Answer:
The quadratic variation equation for the relatonship is:
Answer:
5
Step-by-step explanation:
same x coordinate
length = 3 + 2 = 5