The total of the running backs' salaries need to be added together first. So, $1 000 000 + $850 000 + $750 000 + $500 000 = $3 100 000. Now we divide the total number of salaries by the running back salaries: $3 100 000/$33 000 000 = 0.094 x 100 = 9.4 %.
Round off to nearest percent = 9.00 %.
Answer: The answer is (C).
Step-by-step explanation: The given statement is - "Two matrices are row equivalent if they have the same number of rows". We are to explain whether the statement is true or false.
What are row equivalent matrices? The answer to this question is -
Two matrices are said to be row equivalent if one of the matrices can be obtained from the other by applying a number of elementary row operations. Or, we can say two matrices of same order are row equivalent if they have same row space.
Thus, the correct option is (C).
Answer:
The fourth term of the expansion is -220 * x^9 * y^3
Step-by-step explanation:
Question:
Find the fourth term in (x-y)^12
Solution:
Notation: "n choose k", or combination of k objects from n objects,
C(n,k) = n! / ( k! (n-k)! )
For example, C(12,4) = 12! / (4! 8!) = 495
Using the binomial expansion formula
(a+b)^n
= C(n,0)a^n + C(n,1)a^(n-1)b + C(n,2)a^(n-2)b^2 + C(n,3)a^(n-3)b^3 + C(n,4)a^(n-4)b^4 +....+C(n,n)b^n
For (x-y)^12, n=12, k=3, a=x, b=-y, and the fourth term is
C(n,3)a^(n-3)b^3
=C(12,3) * x^(12-3) * (-y)^(3)
= 220*x^9*(-y)^3
= -220 * x^9 * y^3
Answer:
1
The probability is 
2
The probability is 
Step-by-step explanation:
From the question we are told that
The population mean is 
The standard deviation is 
The sample size is 
Generally the standard error for the sample mean 
is mathematically evaluated as
substituting values
Apply central limit theorem[CLT] we have that
![P(\= X < 33) = [z < \frac{33 - \mu }{\sigma_{\= x}} ]](https://tex.z-dn.net/?f=P%28%5C%3D%20X%20%3C%2033%29%20%3D%20%20%5Bz%20%3C%20%20%5Cfrac%7B33%20-%20%20%5Cmu%20%7D%7B%5Csigma_%7B%5C%3D%20x%7D%7D%20%5D)
substituting values
![P(\= X < 33) = [z < \frac{33 - 28.29 }{4.48} ]](https://tex.z-dn.net/?f=P%28%5C%3D%20X%20%3C%2033%29%20%3D%20%20%5Bz%20%3C%20%20%5Cfrac%7B33%20-%20%2028.29%20%7D%7B4.48%7D%20%5D)
![P(\= X < 33) = [z < 1.05 ]](https://tex.z-dn.net/?f=P%28%5C%3D%20X%20%3C%2033%29%20%3D%20%20%5Bz%20%3C%20%201.05%20%5D)
From the z-table we have that
For the second question
Apply central limit theorem[CLT] we have that
![P(\= X > 30 ) = [z > \frac{30 - \mu }{\sigma_{\= x}} ]](https://tex.z-dn.net/?f=P%28%5C%3D%20X%20%3E%2030%20%29%20%3D%20%20%5Bz%20%3E%20%20%5Cfrac%7B30%20-%20%20%5Cmu%20%7D%7B%5Csigma_%7B%5C%3D%20x%7D%7D%20%5D)
substituting values
![P(\= X < 33) = [z > \frac{30 - 28.29 }{4.48} ]](https://tex.z-dn.net/?f=P%28%5C%3D%20X%20%3C%2033%29%20%3D%20%20%5Bz%20%3E%20%20%5Cfrac%7B30%20-%20%2028.29%20%7D%7B4.48%7D%20%5D)
From the z-table we have that
Thus
