# Basic11.8and assemble them for shipping. In order to assess the amount of time his assemblers devote tothis task, the retailer takes a random sample of 100 orders and records the number of items ineach order (Noltems) and the time needed to assemble the shipment.An online retailer needs to manage the amount of time needed to select the ordered itemsTime4.8 14.7 13.7 9.5 2.4 11.8 10.5 12.0 14.3 16.4 17.9 14.5 16.7 20.1 16.8Noltems 3 3 3 3 3 44 4 44 4 445Time20.8 26.8 12.9 13.0 15.4 10.8 20.3 22.3 20.0 21.9 20.7 20.9 19.9 17.1 19.1NoItems 5 55 5 6 6Time6 666 6 777717.2 18.1 17.9 12.9 19.6 27.9 22.2 23.2 17.5 15.3 21.8 17.9 20.1 18.9 29.3Noltems 78 8 8 888 9999 910 10 10Time21.5 26.5 28.2 25.1 26.1 28.2 22.3 21.8 25.5 24.4 18.1 26.7 24.6 30.1 21.5Time25.2 28.2 22.6 31.3 27.2 28.8 29.7 34.3 27.9 29.7 28.7 34.6 38.0 28.0 37.0NoItems 17 18 18 18 19 20 21 22 23 24 2525 25 26 27Time32.5 39.5 39.0 37.0 35.5 38.3 44.0 39.6 42.3 34.6 44.9 47.4 49.2 45.8 44.0NoItems 27 30 30 31 37 39 40 41 45 46Time46.1 42.9 48.3 46.0 48.2 54.7 49.9 55.4 57.1 52.4b. Fit a least-squares line to the data, and comment on the degree of fit to the data.c. Fit a regression model with the square root of Noltems as the explanatoryvariable.d. Which model produced a better fit to the data?

Question
Asked Apr 2, 2019
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Step 1

Given data of sample of 100 orders with number of items in each order and time needed to assemble the shipment as shown below.

Here let us use an excel sheet to find the best fit line for the given data. So first let us enter all the given data in two coloumns number of items and time in an excel sheet.

Step 2

Now let us plot the scatter plot of the data and then add the best fit trend line to it. It give us the best fit linear line as y = 1.065x + 14.585 with coefficient of determination         &nbs...

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