The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 90% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2676 thousand. The equation of the regression line is y = 1.205x+ 405.157. Company 1, x Company 2, y | 1907 2190 4104 3964 3568 3421 3343 3063 2855 2458 1936 1668 4928 4824 4799 4706 4603 4443 4083 3816 2953 2005 when the number of new vehicles sold by Company 1 is 2676 thousand. Select the correct choice below and fill in the answer boxes to complete your choice. Construct and interpret a 90% prediction interval for new-vehicle sales for Company (Round to the nearest cent needed.) O A. We can be 90% confident that when the new-vehicle sales for Company 1 is 2676 thousand, the new-vehicle sales for Company 2 will be between and thousand. O B. There is a 90% chance that the predicted new-vehicle sales for Company 2 is between and thousand, given that the new-vehicle sales for Company 1 is 2676 thousand.

The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 90% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2676 thousand. The equation of the regression line is y = 1.205x+ 405.157. Company 1, x Company 2, y | 1907 2190 4104 3964 3568 3421 3343 3063 2855 2458 1936 1668 4928 4824 4799 4706 4603 4443 4083 3816 2953 2005 when the number of new vehicles sold by Company 1 is 2676 thousand. Select the correct choice below and fill in the answer boxes to complete your choice. Construct and interpret a 90% prediction interval for new-vehicle sales for Company (Round to the nearest cent needed.) O A. We can be 90% confident that when the new-vehicle sales for Company 1 is 2676 thousand, the new-vehicle sales for Company 2 will be between and thousand. O B. There is a 90% chance that the predicted new-vehicle sales for Company 2 is between and thousand, given that the new-vehicle sales for Company 1 is 2676 thousand.

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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?
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. The equation of the regression line is y=1.228x+331.966 Company_1,_x Company_2,_y4093 49293976 48203557 48003411 47323296 46193102 44872859 40482488 38091970 29191625 20021946 2176 Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) A. There is a 99% chance that the predicted new-vehicle sales for Company 2 is between enter your response here and enter your response here thousand, given that the new-vehicle sales for Company 1 is 2600 thousand.…
The table below shows the numbers of new-vehicle sales (in thousands) for Company 1 and Company 2 for 11 years. Construct and interpret a 99% prediction interval for new-vehicle sales for Company 2 when the number of new vehicles sold by Company 1 is 2600 thousand. The equation of the regression line is y=1.228x+331.966 Company_1,_x Company_2,_y4093 49293976 48203557 48003411 47323296 46193102 44872859 40482488 38091970 29191625 20021946 2176
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. The equation of the regression line is y=32.824x+17,659.242. Issues, x 418 475 683 477 492 379 59 51 196 154 Proceeds, y 17,703 28,601 43,966 31,686 36,833 36,916 21,908 10,311 31,407 28,337 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 646. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. We can be 95% confident that when there are 646 issues, the proceeds will be between $____ and $____. B. There is a 95% chance…
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states, where xx is thousands of automatic weapons and yy is murders per 100,000 residents. xx 11.3 8.2 7.1 3.7 2.9 2.2 2.1 0.6 yy 13.9 10.7 10.3 7.2 6.5 5.6 5.5 4.6 Use your calculator to determine the equation of the regression line and write it in the y=ax+by=ax+b form. Round to 2 decimal places. According to this model, how many murders per 100,000 residents can be expected in a state with 4.6 thousand automatic weapons? Round to 3 decimal places. According to this model, how many murders per 100,000 residents can be expected in a state with 4.4 thousand automatic weapons? Round to 3 decimal places.
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 569.The equation of the regression line is y=32.409x+17,285.501. Issues, x 410 467 679 499 497 394 62 53 189 174 Proceeds, y 18,223 28,066 43,757 31,337 35,488 35,312 22,180 10,660 30,384 28,416 Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 569. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. There is a 95% chance that the predicted proceeds given 569 issues is between $____ and $____. B. We can be 95% confident…
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings(in millions) are shown in the table. The equation of the regression line is y=47.538x+18,727.65. Complete parts a and b. Issues, x Proceeds, y 423 18,632 460 27,913 687 44,071 485 32,435 500 66,634 389 66,734 57 22,180 65 11,296 188 31,929 163 27,891 (a) Find the coefficient of determination and interpret the result. How can the coefficient of determination be interpreted? (b) Find the standard error of estimate se and interpret the result. How can the standard error of estimate be interpreted?
The following table displays the mathematics test scores for a random sample ofcollege students, along with their final SY16C grades.a. Fit the regression line y=a+bx to the data and interpret the results.b. Use the regression equation to determine the SY16C grade for a college student whoscored 60 on their achievement test. What would their SY16C gradebe? Mathematics test(x) SY16C grades(y)1 39 652 43 783 21 524 64 825 57 926 47 897 28 738 75…
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The table below shows the numbers of new-vehicle sales for company 1 and company 2 for 11 years. Construct and interpret a 90% prediction interval for new vehicle sales for company 2 when the number of new vehicles sold by company 1 is 2687 thousand. The equation of the regression line is y = 1.207x + 398.378 "We can be 90% confident that when the new-vehicle sales for company 1 is 2687 thousand, the new-vehicle sales for company 2 will be between ___ and ___ thousand."
The marketing manager of a supermarket chain would like to determine the effect of shelf spaceon the sales of pet food. A random sample of 10 stores was selected, and the results are presentedbelow. Store shelf space in cm weekly sales in thousand pesos 1 45 18 2 45 21 3 75 15 4 80 18 5 95 23 6 100 26 7 135 22 8 140 27 9 185 25 10 190 28 d. Using the estimated simple linear regression equation Y=15.6414+0.0611X, estimate the weekly sales when theshelf space is 230cm? 250cm? e. Compute the coefficient of determination and interpret its value.