# Quiz of Dan Barrett

As stated by the creators of the song, Ã¢ï¿½ï¿½Puff the Magic DragonÃ¢ï¿½ï¿½ symbolized a young boyÃ¢ï¿½ï¿½s fall towards adulthood through the loss of imagination. Throughout this entire song, Puff stood for imagination, while Jackie Paper signified the boy who was changing. Early quotes showing that Ã¢ï¿½ï¿½Together they would travel/On a boat with billowed sail/Jackie kept a lookout perched On Puff's gigantic tail,Ã¢ï¿½ï¿½ indicated that Jackie was using his imagination with help from Puff. However, the theme of the story changes when the pain of adulthood arrives and prevents Jackie from entering the land of Honah Lee.

The quote â€œPainted wings and giant rings/Make way for other toys,â€ showed that adolescent imagination would make way for the troubles of adulthood. Towards the end of the poem, the quote, â€œWithout his life-long friend/ Puff could not be brave/ So Puff that mighty dragon/Sadly slipped into his caveâ€ showed that since Jackie crossed into maturity, the need for a childhood imagination became superfluous. As a result, Puff decided to go back into his cave. With Puff out of the picture, Jackie Paperâ€™s character grew up to tackle adulthood without his imagination.

Created by: Dan Barrett
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2. What is your gender?
1. What is the residual of a point that lies at (12, 169) if the slope of the least square regression line for the data the point lies in is y(hat) = - 345 + 42.55 x ?
2. (0,12.5) (.5,26) (1,36.5) (1.5,44) (2,48.5) (2.5,50) (3,48.5) (3.5,44) (4,36.5) Which is the most appropriate equation for a linear model that represents the data? (b = constant, a = constant)
3. If r = .8995 for a set of data, what is the percent that the two variables in this set of data are related?
4. Studies show that people with higher salaries are often fatter than people with low salaries. Is this relationship causitive, common response, or cofounding?
5. The following are the points for the residual set of the transformation of some data points: (8,2) (9,.8) (10,-.2) (11, -1.2) (12, -1.8) (13, -1.5) (14,-1) (15, .5) (16, 2.5) How well does this line fit the transformed data?
6. Which of the following may be an exponential model of some data set?
7. If the least square regression line for the number of television sets per per person per household is y(hat) = .6x + 2.5, how many televisions would you predict to be in a household with 3 people?
8. If one can determine the predicted hieght of a child based on how much milk the child drinks, which is the explanatory variable?
9. If a data set had an r-value of -.99, how would you describe the correlation?
10. The line y(hat) = a + bx always passes through:

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