Answer:
The product of 9 and -7 is -63
Step-by-step explanation:
Hope This Helped!
Answer:
Step-by-step explanation:
1.From the given triangle, ABC, using the proportionality theorem, we get
⇒
⇒
Thus, the height will be 25 feet.
2.
Statement Reason
1.∠C≅∠E Given
2. ∠ABC≅∠DBE Vertically opposite angles
3. ΔABC is similar to ΔDBE AA similarity rule.
Answer:
d. An additional month of buying and selling is associated with an additional $417 in profits.
Step-by-step explanation:
We have general form of intercept form of equation:
y = m*x + c ----- (A)
Given equation is : y = 2502 + 417*x
Rewrite equation: y = 417*x + 2502 ------(B)
comparing equation (B) with equation (A), we get
m = 417 (additional benefits per month) because multiplied factor x is the month.
Answer:
1st odd = 57
2nd odd = 59
3rd odd = 61
Step-by-step explanation:
Suppose the numbers to be:
1st odd = x -2
2nd odd = x
3rd odd = x +2
Now according to given conditions:
1st odd + 2nd odd + 3rd odd = 177
x - 2 + x +x + 2 = 177
By add -2 and + 2 will be cancelled
Adding all x
3x = 177
Dividing both sides by 3 we get
x = 177 / 3
x = 59
Now putting x = 59 to get three consecutive odds:
1st odd = x -2 = 59 - 2 = 57
2nd odd = x = 59
3rd odd = x +2 = 59 + 2 = 61
Proof:
1st odd + 2nd odd + 3rd odd = 177
57 + 59 + 61 = 177
177 = 177
hence proved
I hope it will help you!
Answer:
(a) Shown below
(b) There is a positive relation between the number of assemblers and production.
(c) The correlation coefficient is 0.9272.
Step-by-step explanation:
Let <em>X</em> = number of assemblers and <em>Y</em> = number of units produced in an hour.
(a)
Consider the scatter plot below.
(b)
Based on the scatter plot it can be concluded that there is a positive relationship between the variables <em>X</em> and <em>Y</em>, i.e. as the value of <em>X</em> increases <em>Y</em> also increases.
(c)
The formula to compute the correlation coefficient is:
![r=\frac{n\sum XY-\sum X\sum Y}{\sqrt{[n\sum X^{2}-(\sum X)^{2}][n\sum Y^{2}-(\sum Y)^{2}]}} }](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%5Csum%20XY-%5Csum%20X%5Csum%20Y%7D%7B%5Csqrt%7B%5Bn%5Csum%20X%5E%7B2%7D-%28%5Csum%20X%29%5E%7B2%7D%5D%5Bn%5Csum%20Y%5E%7B2%7D-%28%5Csum%20Y%29%5E%7B2%7D%5D%7D%7D%20%7D)
Compute the correlation coefficient between <em>X</em> and <em>Y</em> as follows:
![r=\frac{n\sum XY-\sum X\sum Y}{\sqrt{[n\sum X^{2}-(\sum X)^{2}][n\sum Y^{2}-(\sum Y)^{2}]}} }=\frac{(5\times430)-(15\times120)}{\sqrt{[(5\times55)-15^{2}][(5\times3450)-120^{2}]}} =0.9272](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%5Csum%20XY-%5Csum%20X%5Csum%20Y%7D%7B%5Csqrt%7B%5Bn%5Csum%20X%5E%7B2%7D-%28%5Csum%20X%29%5E%7B2%7D%5D%5Bn%5Csum%20Y%5E%7B2%7D-%28%5Csum%20Y%29%5E%7B2%7D%5D%7D%7D%20%7D%3D%5Cfrac%7B%285%5Ctimes430%29-%2815%5Ctimes120%29%7D%7B%5Csqrt%7B%5B%285%5Ctimes55%29-15%5E%7B2%7D%5D%5B%285%5Ctimes3450%29-120%5E%7B2%7D%5D%7D%7D%20%3D0.9272)
Thus, the correlation coefficient is 0.9272.