Answer:

But we need to calculate the mean with the following formula:

And replacing we got:

And for the sample variance we have:

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance 

Step-by-step explanation:
For this case we have the following data:
1.04,1.00,1.13,1.08,1.11
And in order to estimate the population variance we can use the sample variance formula:

But we need to calculate the mean with the following formula:

And replacing we got:

And for the sample variance we have:

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance 

I got C but not sure if that is right
L•w=102
l=8w+6
8w+6•w=102
9w+6=102
102-6=96
9w=96
96/9= 10.67
Width is 10.67 yards
Remember that the slope intercept formula is:
y = mx + b
m is the slope
b is the y-intercept
so...
m = 0
b = -2
^^^Plug these numbers into formula
y = 0*x - 2
y = 0 - 2
y = -2
Hope this helped!
~Just a girl in love with Shawn Mendes