The quantity ˆB used in ratio estimation is sometimes called the ratio-of-means estimator. An alternative that has been proposed is the mean-of-ratios estimator: Let bi = yi/xi for unit i; then the mean-of-ratios estimator is ¯b = 1 n i∈S bi. a Doyou think the mean-of-ratios estimator is appropriate for the data in Example 4.5? Why, or why not? b Show that, for the ratio-of-means estimator ˆB, tx ˆB = ty when the entire population is sampled (i. e., S = U). c Give an example to show that it is possible to have tx ¯b = ty when the entire population is sampled. d Define Sbx = 1 N − 1 N i=1 (bi − ¯bU)(xi − ¯xU). Show that for an SRS of size n, the bias of ¯b as an estimator of B is E[¯b − B] = −(N − 1)Sbx tx . As a consequence, if Sbx = 0 the bias does not decrease as n increases. e (Requires linear model theory.) Showthat ¯b is the weighted least squares estimator of β under the model Yi = βxi + εi

step-by-step explanation:

if you want to solve percent error follow these steps.

1. subtract the accepted value from the experimental value.

2. take the absolute value of step 1.

3. divide that answer by the accepted value.

4. multiply that answer by 100 and add the % symbol to express the answer as a percentage.

if you want to solve percent of change just do this.

1. work out the difference (increase) between the two numbers you are comparing.

2. divide the increase by the original number and multiply the answer by 100. if your answer is a negative number then this is a percentage decrease.

hope this : )

dont know

step-by-step explanation:

table a is wierd

step-by-step explanation:

6*f

f . i can go whenever i feel like it bc it is confidential meaning only i would know how much i deposited besides the bank and they wouldnt care bc when you make a deposit you are using their services which means they are using there competition and gaining more customers

and if they dont well then thats less customers for them in a less profitable way

plz mark brainliest