The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (inmillions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number ofissues is 628. The equation of the regression line is y = 31.645x+17,909.644.^187154451 698 475 494 386 62 6618,700 28,176 44,414 31,249 35,820 35,165 21,462 12,081 31,272 28,256|Issues, x424Proceeds, yClick the icon to view a table of critical values for the t-distribution.Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 628.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 628 issues is between $and $B. We can be 95% confident that when there are 628 issues, the proceeds will be between $and $

Step 1: Use the Regression EquationThe regression equation is: y^=31.645x+17,909.644…

Answered: The number of initial public offerings…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.5*SM_DOLLARS + 0.5*RADIO_ADS + 0.8*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $108 without changing the amount spent on radio ads or web search ads? (Round your answer to the nearest whole number.)
The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table. Time Miles Load Speed Oil 7.7 42.9 22.0 44.0 16.0 0.8 98.3 20.0 47.0 34.0 6.3 61.1 22.0 62.0 15.0 E Click here for the Excel Data File b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Time = Miles Load Speed oil + + d. What is the predicted time before the first engine overhaul for a particular truck driven 60,000 miles per year with an average load of 25 tons, an average driving speed of 53 mph, and 21,000 miles…
Create a model for the data using the 1st and 3rd points in the data set. 1909 90.490 1st point^ 1929 121.767 3 rd point ^ y= years since 1909 P=population of the United States (in millions)
Can that regression be used to estimate the effect of the national unemployment rate on an individual’s earnings? Explain.
Define Residuals or errors in Alternative Regression Models?
The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend Interpret the y-intercept of the regression line in context.
Describe how correlation and regression are linked yet distinct.
A frequent flyer was interested in the relationship between dollars spent on flying and the distance flown. She sampled 20 frequent flyers of a certain airline. She collected the number of miles flown in the previous year and the total amount of money the flyer spent. A regression line of distance flown on money spent was fit to the data: \hat y = 24000 + 10xy^=24000+10x. A person who spent $1000 is predicted to have flown:
If you have 2 datasets on which you have conducted a regression analysis, how would you determine whether you can combine them into one dataset?
Find the regression line of the points: (1, 9), (2, 8), (8, 4), (9, 2)
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…

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