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 thetotal square footage is 5.7 billion. The equation of the regression line is y = 567.939x - 1985.560.Total4.9 5.2 5.3 5.45.55.65.95.9 5.9 6.1Square Footage, xSales, y880.1 935.5 989.5 1056.9 1100.7 1201.9 1283.4 1346.3 1434.8 1549.5Click the icon to view a table of critical values for the t-distribution.Construct a 90% prediction interval for the sales when the total square footage is 5.7 billion. Choose the correct prediction interval below, rounded to the nearest million dollars. $116,152,000,000$0$1,367,844,000,000$37,010,000,000$1,135,540,000,000

Answered: Image /qna-images/answer/071c686d-91c3-4246-952a-8ee855d3d92b.jpg

Answered: The table shows the total square…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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Find the mean hourly cost when the cell phone described above is used for 240 minutes.
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Does Table 1 represent a linear function? If so, finda linear equation that models the data.
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) PICK THE CORRECT ANSWER [A] We can be 98% confident that when the average weekly wages of state government employees is $878, the average weekly wages of…
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construct and interpret a 99% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,634 thousand barrels per day. The equation of the regression line is y=- 1.190x+16,230.863. Oil produced, x 5,811 5,659 5,450 5,168 5,094 Oil imported, y 9,320 9,621 10,030 10,126 10,157 5,739 9,118 LL OA. There is a 99% chance that the predicted amount of oil imported is between per day produced. 5,049 10,066 Construct and interpret a 99% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,634 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to two decimal places as needed.) and…
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construct and interpret a 98% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y=-1.106x+15,759.462 Oil_produced,_x Oil_imported,_y5,816 9,3455,741 9,1245,660 9,6325,405 10,0095,155 10,1685,059 10,1055,015 10,055
What is meant by the slope of the regression line?
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construc and interpret a 90% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,542 thousand barrels per day. The equation of the regression line is y = - 1.248x + 16,547.218. Oil produced, x Oil imported, y 5,759 9,307 5,724 9,146 5.642 9,611 5,482 10,011 5,199 10,185 5,092 10,116 5,052 10,088 2 Construct and interpret a 90% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,542 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to two decimal places as needed.) O A. There is a 90% chance that the predicted amount of oil imported is between and thousand barrels…
Suppose that for a typical FedEx package delivery, the cost of the shipment is a function of the weight of the package measured in ounces. You want to try to predict the cost of a typical shipment given package dimensions. If 10 packages in a city are sampled and the regression output is given below, report the regression equation. 1) (cost of delivery) = 1.468*(weight) - 23.015 2) (weight) = -23.015*(cost of delivery) + 1.468 3) (cost of delivery) = -23.015*(weight) + 1.468 4) (cost of delivery) = 1.468*(weight) 5) (weight) = 1.468*(cost of delivery) - 23.015

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