Answer:
x = 13 ,y = 60
Step-by-step explanation:
Solve the following system:
{2 x + 6 y = 386 | (equation 1)
4 x + 4 y = 292 | (equation 2)
Swap equation 1 with equation 2:
{4 x + 4 y = 292 | (equation 1)
2 x + 6 y = 386 | (equation 2)
Subtract 1/2 × (equation 1) from equation 2:
{4 x + 4 y = 292 | (equation 1)
0 x+4 y = 240 | (equation 2)
Divide equation 1 by 4:
{x + y = 73 | (equation 1)
0 x+4 y = 240 | (equation 2)
Divide equation 2 by 4:
{x + y = 73 | (equation 1)
0 x+y = 60 | (equation 2)
Subtract equation 2 from equation 1:
{x+0 y = 13 | (equation 1)
0 x+y = 60 | (equation 2)
Collect results:
Answer: {x = 13 ,y = 60
Answer: The answer is 10 inches.
Step-by-step explanation: Given that the area of a trapezoid is 50 square inches and the bases are 3 inches and 7 inches. We are to find the height of the trapezoid.
We know that the area of a trapezoid with height 'h' and bases 'a' inches and 'b' inches is given by

In the given question,
a = 3 inches, b = 7 inches, A = 50 square inches, h = ?
Therefore,

Thus, the required height is 10 inches.
Answer:
For this case we need to check the conditions in order to use the normal approximation:
1) 
2) 
Since both conditions are satisfied and the independence condition is assumed we can use the normal approximation given by:

The mean would be given by:

And the deviation is given by:

Step-by-step explanation:
For this case we know the following info:
n =60 represent the sample size
represent the estimated proportion of people that will buy a packet of crackers after tasting
For this case we need to check the conditions in order to use the normal approximation:
1) 
2) 
Since both conditions are satisfied and the independence condition is assumed we can use the normal approximation given by:

The mean would be given by:

And the deviation is given by:

Answer:
1
Step-by-step explanation:
Given the question above :
The probability distribution :
X : ___ 1 ___ 2 ___ 3 ___ 4 ____ 5
P(x): _ 0.1 __ 0.1 __ 0.6 _ 0.1 __ 0.1
The Variance : Var(X) = (Σx²*p(x)) - μ²
μ = E(X) = Σ(X * p(x)) :
Σ(X * p(x)) = (1*0.1)+(2*0.1)+(3*0.6)+(4*0.1)+(5*0.1)
μ = 3
Var(X): [(1^2*0.1)+(2^2*0.1)+(3^2*0.6)+(4^2*0.1)+(5^2*0.1)] - 3²
= 10 - 9
= 1
Hence. Variance = 1
Six is thousandths four is hunderdths one is ones and tens is 20 i think