Answer:
8.5
Step-by-step explanation:
Answer:
Step-by-step explanation:
-5x - 10y = -30
5x + 3y = 2
-7y = -28
y = 4
x + 8 = 6
x = -2
(-2, 4)
Answer: 1/36
Step-by-step explanation: 2/9 x 1/8 =2/72 = 1/36
Answer:
X is the GPA
Y is the Salary
Standard deviation of X is 0.4
Standard deviation of Y is 8500
E(X)=2.9
E(Y)=47200
We are given that The correlation between the two variables was r = 0.72
a)![y = a+bx](https://tex.z-dn.net/?f=y%20%3D%20a%2Bbx)
![b = \frac{\sum(x_i-\bar{x})(y_i-\bar{y})}{\sum(x_i-\bar{x})^2} = \frac{r \times \sqrt{var(X) \times Var(Y)}}{Var(X)} = \frac{0.72 \times \sqrt{0.4^2 \times 8500^2}}{0.4^2} = 15300](https://tex.z-dn.net/?f=b%20%3D%20%5Cfrac%7B%5Csum%28x_i-%5Cbar%7Bx%7D%29%28y_i-%5Cbar%7By%7D%29%7D%7B%5Csum%28x_i-%5Cbar%7Bx%7D%29%5E2%7D%20%3D%20%5Cfrac%7Br%20%5Ctimes%20%5Csqrt%7Bvar%28X%29%20%5Ctimes%20Var%28Y%29%7D%7D%7BVar%28X%29%7D%20%3D%20%20%5Cfrac%7B0.72%20%5Ctimes%20%5Csqrt%7B0.4%5E2%20%5Ctimes%208500%5E2%7D%7D%7B0.4%5E2%7D%20%3D%2015300)
![a=y-bx = 47200-(15300 \times 29) = 2830](https://tex.z-dn.net/?f=a%3Dy-bx%20%3D%2047200-%2815300%20%5Ctimes%2029%29%20%3D%202830)
So, slope = 15300
Intercept = 2830
So, equation : ![y = 2830+15300x](https://tex.z-dn.net/?f=y%20%3D%202830%2B15300x)
b) Your brother just graduated from that college with a GPA of 3.30. He tells you that based on this model the residual for his pay is -$1880. What salary is he earning?
![y = 2830+15300 \times 3.3 = 53320](https://tex.z-dn.net/?f=y%20%3D%202830%2B15300%20%5Ctimes%203.3%20%3D%2053320)
Observed salary = Residual + predicted = -1860+53320 = 51440
c)) What proportion of the variation in salaries is explained by variation in GPA?
The proportion of the variation in salaries is explained by variation in GPA = ![r^2 = (0.72)^2 =0.5184](https://tex.z-dn.net/?f=r%5E2%20%3D%20%280.72%29%5E2%20%3D0.5184)
Answer:
x=3
Step-by-step explanation:
try different values on the line! plug them in and you'll see that every x value is 3!