Simplified it's 576x^8y^7
Answer:
7 ( 7 g + 9 y )
Step-by-step explanation:
thats the answer
Answer:
Area = 6.25
ft^2
Step-by-step explanation:
Area = 

The diameter is 5 feet. That makes the radius 2.5 feet
Area = 

Area = 

Area = 6.25
ft^2
Answer:
Null hypothesis:
Alternative hypothesis:
The statistic to check the hypothesis is given by:
And is distributed with n-2 degrees of freedom
And the statistic to check the significance of a coeffcient in a regression is given by:

For this case is importantto remember that t1 and p value for test of slope coefficient is the same test statistic and p value for the correlation test so then the answer would be:
Always
Step-by-step explanation:
In order to test the hypothesis if the correlation coefficient it's significant we have the following hypothesis:
Null hypothesis:
Alternative hypothesis:
The statistic to check the hypothesis is given by:
And is distributed with n-2 degrees of freedom
And the statistic to check the significance of a coeffcient in a regression is given by:

For this case is importantto remember that t1 and p value for test of slope coefficient is the same test statistic and p value for the correlation test so then the answer would be:
Always