A least squares regression line was calculated to relate the length (cm) of newbom boys to their weight in kg. The line is weight=-6.06 +0.1768 length. Explain in words what this model means. Should new parents (who tend to worry) be concermed if their newborn's length and weight don'Y fit this equation? What does the given model mean? OA The minimum length of a newborn baby boy can be no less than 34 276 cm. OB. The weight of a newbom boy will always equal -6.06 kg plus 0.1768 kg per cm of length. OC. The weight of a newborn boy can be predicted as -6.06 kg plus 0.1768 kg per cm of length. O D. The length of a newborn boy can be predicted as -6.06 cm plus 0.1768 cm per kg of weight

A least squares regression line was calculated to relate the length (cm) of newbom boys to their weight in kg. The line is weight=-6.06 +0.1768 length. Explain in words what this model means. Should new parents (who tend to worry) be concermed if their newborn's length and weight don'Y fit this equation? What does the given model mean? OA The minimum length of a newborn baby boy can be no less than 34 276 cm. OB. The weight of a newbom boy will always equal -6.06 kg plus 0.1768 kg per cm of length. OC. The weight of a newborn boy can be predicted as -6.06 kg plus 0.1768 kg per cm of length. O D. The length of a newborn boy can be predicted as -6.06 cm plus 0.1768 cm per kg of weight

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?
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A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.69 + 0.1656 length. A newborn was 48cm long and weighed 33kg. According to the regression model, what was his residual? What does that say about him?
the least squares regression line for predicting the temperature from the chirp rate is y=32.298+12.297x. If the two chirp rates differ by 1.5 chirps per second, by how much would the temperature differ?
A regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The least squares regression line is weight = -5.94 + 0.1875 length. Explain in words what this model means (slop and intercept) The new- born boy was 48 cm long, what is the predicted weight of this boy? It is known that the boy is weighed 3 kg. what was his residual? What does that say about him?
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A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight=−5.59+0.1826 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?
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