<span>What is r = wp, for p
</span>r = wp...divide both sides by w
so then p = r/w
If you would like to know how much of the damages will the insurance company have to pay, you can calculate this using the following steps:
x% of $32000 is $25000
x% * 32000 = 25000
x/100 * 32000 = 25000
x * 320 = 25000
x = 25000 / 320
x = 78.125%
The insurance company will have to pay 78.125% of the damages.
Answer:
so the closet value will be 21.
Step-by-step explanation:
In this question we have to calculate the value of 85% of 25.
To calculate the percentage first we have to write percentage to the fraction and then multiply with 25.
× 25
= 0.85 × 25
= 21.25
Therefore, the closet value of 21.25 will be 21 because when we round off, 0.25 will be waved off. Had this value been greater than 0.50 or equal to 0.5 than this value would have been 22.
so the closet value will be 21.
Answer:
P(L ∩ <u>O)</u> = 0.23
Step-by-step explanation:
We are going to define the probabilistic events how:
E: Flights arrive early P(E) =0.15
T: Flights arrive on time P(T) = 0.25
O: Flights are overbooked P(O) = 0.65
<u>O</u>: Flights are not overbooked
L: Flights arrive late
How 72 percent are late or not overbooked, then P(<u>O</u> ∪ L ) = 0.72
Our question is : What is the probability that the flight selected will be late and not overbooked? It means, what is P(L ∩ <u>O)</u>
This probability may be calculated how:
P(L ∩ <u>O)</u> = P(L) + P (<u>O</u>) - P(<u>O</u> ∪ L )
1 = P(L) + P(E) + P(O)
1 = P(L) + 0.15 + 0.25
P(L) = 0.6
how P(0) = 0.65, then P(<u>O</u>) = 0.35
Thus
P(L ∩ <u>O)</u> = 0.6 + 0.35 - 0.72
P(L ∩ <u>O)</u> = 0.23
Answer:
reject H₀ , {0.8262, 3.1738} at 99% C I
Step-by-step explanation:

critical value, 
degree of freedom: 35 - 1 = 34
critical value: 2.441
from the expression


t = 4.648 > 2.441
H₀ is rejected because t > critical value
(b)
in the second scenario

1 - 0.99 = 0.01

degree of freedom = 34
t = 2.728
substituting in the above formula
we have


![I:[0.8262, 3.1738]](https://tex.z-dn.net/?f=I%3A%5B0.8262%2C%203.1738%5D)
we can see the difference of the means is between 0.8262 and 3.1738 at 99% confidence