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Homework 6 results. 1.a Y = 150X + 200 Y = 200 + 150X Six minutes of flight . . . Y = 150*6 + 200 Y = 1100. 1.b. Car rental Y = .06X + 29 Y = 29 + .06X Rental for 200 miles . . . Y = .06 * 200 + 29 Y = $41.00.

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1 b car rental y 06x 29 y 29 06x rental for 200 miles y 06 200 29 y 41 00
1.b. Car rental Y = .06X + 29 Y = 29 + .06XRental for 200 miles . . . Y = .06 * 200 + 29 Y = $41.00
slide7
2.d.: The function is linear because the change in Y is constant across all values of X. For every $100 spent, exactly $20 saved.
3 b predicted 2012 production equation method
3.b. Predicted 2012 production, equation method

Y = -.0606 * 2010 + 122.28

Y = 0.353 billion pounds

3 c confidence in prediction1
3.c. Confidence in prediction

Pro:

  • Strong R-squared
  • Near-term forecast

Con:

  • Imperfections in fit to trendline
  • Possible shift in trend in last four years
4 b prediction of percentage smoking in 2010 equation method
4.b. Prediction of percentage smoking in 2010, equation method

Y = -.4397 * 2010 + 902.23

Y = 18.4%

4 d prediction of percentage smokers in 1953
4.d. Prediction of percentage smokers in 1953

Y = -.4397 * 1953 + 902.23

Y = 43.5%

4 d confidence in prediction1
4.d Confidence in prediction

Pro:

  • Strong fit, R-squared

Con:

  • Many years between 1953 and 1983, so many possible significant economic and social changes
4 e prediction when 100 percent smokers
4.e. Prediction when 100 percent smokers

100 = -.4397 * X + 902.23

100-902.23 = -.4397 * X

-802.23/-.4397 = X

1824 = X

5 a main point of article
5.a Main point of article

Projections of the percentage of the population

who will be obese in 40 years

is quite dubious

if not totally bogus. 

5 b relevance to linear models
5.b Relevance to linear models

It makes exactly the same point

about projections far into the future

as we considered

with regard to the number of motor vehicles and  consumption of coal

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