Determine the best curvilinear trendline that maximizes R OA. The best trendline is Exponential with an R? value of The equation is y= (De (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) Data table for number of hours per helicopter O B. The best trendline is Power with an R value of. The equation is y = (Dx. (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) TT Helicopter Number Labor Hours 2000 OC. The best trendline is Logarithmic with an R? value of The equation is y = O In (x) (Round the coefficient of the logarithm to one decimal place as needed. Round all other values to three decimal places as needed.) 1450 1238 1143 OD. The best trendline is Polynomial with an R value of The equation is y= (Dx+ x+ 1073 1029 989 6 (Round to three decimal places as needed.) 951 Print Done

Determine the best curvilinear trendline that maximizes R OA. The best trendline is Exponential with an R? value of The equation is y= (De (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) Data table for number of hours per helicopter O B. The best trendline is Power with an R value of. The equation is y = (Dx. (Round the coefficient to one decimal place as needed. Round all other values to three decimal places as needed.) TT Helicopter Number Labor Hours 2000 OC. The best trendline is Logarithmic with an R? value of The equation is y = O In (x) (Round the coefficient of the logarithm to one decimal place as needed. Round all other values to three decimal places as needed.) 1450 1238 1143 OD. The best trendline is Polynomial with an R value of The equation is y= (Dx+ x+ 1073 1029 989 6 (Round to three decimal places as needed.) 951 Print Done

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?
A researcher notes that, in a certain region, a disproportionate number of software millionaires were born around the year 1955. Is this a coincidence, or does birth year matter when gauging whether a software founder will besuccessful? The researcher investigated this question by analyzing the data shown in the accompanying table. Complete parts a through c below. a. Find the coefficient of determination for the simple linear regression model relating number (y) of software millionaire birthdays in a decade to total number (x) of births in the region. Interpret the result. The coefficient of determination is 1.___? (Round to three decimal places as needed.) This value indicates that 2.____ of the sample variation in the number of software millionaire birthdays is explained by the linear relationship with the total number of births in the region. (Round to one decimal place as needed.) b. Find the coefficient of determination for the simple linear regression model…
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