Answer:


Step-by-step explanation:
A function and its inverse has the following properties

This implies that;

From the table,

This means that:


Note that: f(7) means the value of f(x) when x=7.
From the table f(x)=-6 when x=7.
That is why f(7)=-6.
Findd total collected
add everybody
fri+sat+sun+mon=
21+5 and 5/6+2.75+4 and 5/8
add what you can
21+5+2.75+4+5/6+5/8=
28.75+5/6+5/8
add the fractions by making denom same
5/6+5/8=20/24+15/24=35/24=1 and 9/24=1 and 3/8
28.75+1 and 3/8=29.75+3/8
that is how many barels total
times 205 since that is how many litesr in each bottle
205 times (29.75+3/8)=
205*29.75+205*(3/8)=
6098.75+76.875=
6175.625
29/30 is lost
1//30 remains
9175.625 times 1/30 (aka divided by 30)=205.854166666666666 litesr
205 bottles (and 0.85 partially full bottle)
Answer:
Step-by-step explanation:
From the given information:
The uniform distribution can be represented by:

The function of the insurance is:

Hence, the variance of the insurance can also be an account forum.
![Var [I_{(x}) = E [I^2(x)] - [E(I(x)]^2](https://tex.z-dn.net/?f=Var%20%5BI_%7B%28x%7D%29%20%3D%20E%20%5BI%5E2%28x%29%5D%20-%20%5BE%28I%28x%29%5D%5E2)
here;
![E[I(x)] = \int f_x(x) I (x) \ sx](https://tex.z-dn.net/?f=E%5BI%28x%29%5D%20%3D%20%5Cint%20f_x%28x%29%20I%20%28x%29%20%5C%20sx)
![E[I(x)] = \dfrac{1}{1500} \int ^{1500}_{250{ (x- 250) \ dx](https://tex.z-dn.net/?f=E%5BI%28x%29%5D%20%3D%20%5Cdfrac%7B1%7D%7B1500%7D%20%5Cint%20%5E%7B1500%7D_%7B250%7B%20%28x-%20250%29%20%5C%20dx)


Similarly;
![E[I^2(x)] = \int f_x(x) I^2 (x) \ sx](https://tex.z-dn.net/?f=E%5BI%5E2%28x%29%5D%20%3D%20%5Cint%20f_x%28x%29%20I%5E2%20%28x%29%20%5C%20sx)
![E[I(x)] = \dfrac{1}{1500} \int ^{1500}_{250{ (x- 250)^2 \ dx](https://tex.z-dn.net/?f=E%5BI%28x%29%5D%20%3D%20%5Cdfrac%7B1%7D%7B1500%7D%20%5Cint%20%5E%7B1500%7D_%7B250%7B%20%28x-%20250%29%5E2%20%5C%20dx)


∴
![Var {I(x)} = 1250^2 \Big [ \dfrac{5}{18} - \dfrac{25}{144}]](https://tex.z-dn.net/?f=Var%20%7BI%28x%29%7D%20%3D%201250%5E2%20%5CBig%20%5B%20%5Cdfrac%7B5%7D%7B18%7D%20-%20%5Cdfrac%7B25%7D%7B144%7D%5D)
Finally, the standard deviation of the insurance payment is:


≅ 404