pleasw help with the following questions please refer to the pictures below

What is the Bullwhip meausre for the retailer? rounded to nearest whole number

2. what is fhe bullwhip measure for the maufacturer?

3. what is the bullwhip measure for the supplier?

4. what conclusions can you draw regarding the impact that economies of scale may have ok the bullwhip effect?

a. larger less frequent orders imply a larger variance of orders

b. larger less frequen orders inply smaller variance of orders

select all correct statements

c. the effect of increasing variance of orders with the less frequent orders could be reduced via channel corrdination by determining lot size

d. the effect of defreasing cariancw of orders with the less frequent orders could be reduced via channel corrdination by determining lot sizes

Consider a three-firm supply chain consisting of a retailer, manufacturer, and supplier. The retailer's demand over an 8-week period was 90 units each of the first 2 weeks, 210 units each of the second 2 weeks, 310 units each of the third 2 weeks, and 400 units each of the fourth 2 weeks. The following table presents the orders placed by each firm in the supply chain. Notice, as is often the case in supply chains due to economies of scale, that total units are the same in each case, but firms further up the supply chain (away from the retailer) place larger, less frequent, orders. Click the icon to view the orders placed by each firm in the supply chain. Click the icon to view the ways of calculating the variance. a) What is the bullwhip measure for the retailer? The bullwhip measure for the retailer is ( Enter your response rounded to two decimal places.) \begin{tabular}{cccc} \hline Week & Retailer & Manufacturer & Supplier \\ \hline 1 & 90 & 180 & 600 \\ 2 & 90 & & \\ 3 & 210 & 420 & \\ 4 & 210 & & \\ 5 & 310 & 620 & 1,420 \\ 6 & 310 & & \\ 7 & 400 & 800 & \\ 8 & 400 & & \\ \hline \end{tabular} Recall that the sample variance of a data set can be found by using the VAR.S function in Excel or by plugging each value x of the data set into the formula: Variance=(n1)(xx)2, where x is the mean of the data set and n is the number of values in the set