Jeff: "So I have a great example

of, one of our warehouses wanted to save some money and

invented a new kind of divider in between inventory on

a shelf, and this divider was made of cardboard,

which was inexpensive.And they installed

these dividers across the whole portion

of the warehouse.They were very

proud of the work, and we were proud of

their scrappiness. And unfortunately though,

after a couple of months, we saw inventory defects

spike in this part of this particular warehouse. We went back to do some deep

dive analytics and inspection to understand why. And it turned out that as

pickers were removing items, they were bumping the

items next to them and slowly they would flatten

some of the cardboard. And so, items from one bin

were drifting into another bin. And when we assigned an

inventory checker to go out to check to see if

the item was there, it was no longer in the

place it was supposed to be. It was in the one next to it,

and that counts as a defect. Because when a

picker comes, they're only looking in the

zone where the software tells them to pick. If it's not there, they note

it as a defect and move on. So we actually were introducing

more customer defects because of this change that was made

to the process."

Let's analyze the inventory sampling data Amazon collected after the implementation of cardboard dividers. In particular, let's construct confidence intenrals to estimate the true inventory defect rate for each of the three different storage types at the warehouse. One of these storage types uses the cardboard divider. Amazon sampled 5,000 observations from each of the three different storage types and recorded \"1\" if there was a defect in the bin and \"0\" if there was not. The mean defect rate and standard deviation for each storage type are provided below. Using a 95% confidence level, calculate your best estimate of the true defect rate of storage type 1. 1 Storage Type Storage Type Storage Type 2 Mean 0.0290 0.0326 0.0586 3 Standard 0.1701 0.1776 0.2349 4 Sample Size 5.000 5.000 5.000 5 6 Lower Bound 7 Upper Bound 8