Answer:
$2647.18
Step-by-step explanation:
Formula : ![A[\frac{1+(\frac{r}{n})^{n}-1 }{(\frac{r}{n} )}]](https://tex.z-dn.net/?f=A%5B%5Cfrac%7B1%2B%28%5Cfrac%7Br%7D%7Bn%7D%29%5E%7Bn%7D-1%20%7D%7B%28%5Cfrac%7Br%7D%7Bn%7D%20%29%7D%5D)
Future value = $43,000
r = rate of interest = 9% = 0.09
t = 3.5 years (compounded quarterly)
n = number of compounding (3.5 × 4) = 14
Now put the values into formula :
43000 = ![A[\frac{1+(\frac{0.09}{4})^{14}-1 }{(\frac{0.09}{4} )}]](https://tex.z-dn.net/?f=A%5B%5Cfrac%7B1%2B%28%5Cfrac%7B0.09%7D%7B4%7D%29%5E%7B14%7D-1%20%7D%7B%28%5Cfrac%7B0.09%7D%7B4%7D%20%29%7D%5D)
43000=A(
43,000 = A(16.243708)
A = 
A = $2,647.17883 ≈ $2647.18
Answer:
y=2x-11
Step-by-step explanation:
Answer:
75
Step-by-step explanation:
The mode is the number that appears most often. Because 75 appears twice and the other numbers only appear once, it is the most used number.
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
