The table shows the total square footage (in billions) of retailing space at sho

Question

The table shows the total square footage (in billions) of retailing space at shopping centers and their sales (in billions of dollars) for 10 years. Construct a 90% prediction interval for sales when the total square footage is 5.6 billion. The equation of the regression line is y 517.730x-1699.919. Total Square Footage 49 51 5.3 52 5.5 5.7 5.B 5.9 6.1 6.1 Sales, y 962.5 934.7988.3 1064.2 1110.4 1206.5 1290.9 1348.7 1449.3 1531.1 90% prediction interval for the sales when the total square footage is 5.6 billion. Choose the correct prediction interval binew, rounded to the nearest million dollars. Interpret the prediction interval. A You can be 90% confident that the sales will be within the prediction interval when the total square footage is 5.6 billion square feet. B, A randomly selected year with 5.6 billion square feet of shopping area has a 90% probability of being within the prediction interval. O c. There is a 90% chance that the predicted sales given 5.6 billion square feet of shopping area is within the prediction interval. (1) O $27.963.000,000 $1,291,698,000,000 (2)$1,107.040,000,000 Oso O $1,107,040,000,000 O $92,328,000,000 o $1,291,698,000,000 $92,328,000,000 O $27,963,000,000

Explanation / Answer

using R

x = c(4.9,5.1,5.3,5.2,5.5,5.7,5.8,5.9,6.1,6.1)
> y = c(862.5,934.7,988.3,1064.2,1110.4,1206.5,1290.9,1348.7,1449.3,1531.1)
> model = lm(y~x)
> predict(model , data.frame(x = 5.6), interval = "prediction",level = 0.90)
       fit                  lwr                upr
1 1199.369      1107.04          1291.698

1) option C) is correct

2) option B) is correct

interpret prediction interval

option A) is correct

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