A substance used in biological and medical research is shipped by air freight to users in cartons of 1,000 ampules. The data below, involving 10 shipments, were collected on the number of times the carton was transferred from one aircraft to another over the shipment route (X) and the number of ampules found to be broken upon arrival (Y). Assume that first-order regression model (1.I) is appropriate. 2 5 7 8 9 10 Xi: Y: 16 9 17 12 22 13 8 15 19 11 0 2 0 2 2.15. Refer to Airfreight breakage Problem 1.21. a Because of changes in airline routes, shipments may have to be transferred more frequently than in the past. Estimate the mean breakage for the following numbers of transfers: X-2, 4. Use separate 99 percent confidence intervals. Interpret your results. b. The next shipment will entail two transfers. Obtain a 99 percent prediction interval for the number of broken ampules for this shipment. Interpret your prediction intervat c. In the next several days, three independent shipments will be made, each entailing two transfers. Obtain a 99 percent prediction interval for the mean number of ampules broken in the three shipments. Convert this interval into a 99 percent prediction interval for the total number of ampules broken in the three shipments.

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Answer:

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Step-by-step explanation:

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The point estimate of the expected number of broken ampules when x = 1 transfer is made from the regression line is 14.2.

How to calculate the regression?

From the given information, the regression equation is y = 10.2 + 4x. The point estimate of the expected number or broken ampules will be:

= 10.2 + 4x

= 10.2 + 4(1)

= 14.2

The expected number of ampules broken when x = 2 will be:

= 10.2 + 4(2)

= 10.2 + 8.

= 18.2

From the given information, x = 1, y = 14.2. We'll substitute the value of x and y in the regression line. Therefore,

14.2 = 10.2 + 4(1)

14.2 = 14.2

In conclusion, the line passes through the point (x, y).

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