1) Given a one independent variable linear equation that states cost in $K, and given the following information, calculate the coefficient of variation and determine its meaning. [removed][removed] | | | | | | | [removed]If we used this equation, we could typically expect to be off by ± 10.77%. | [removed]If we used this equation, we could typically expect to be off by ± 29.31%. | [removed]If we used this equation, we could typically expect to be off by ± 9.32%. | [removed]If we used this equation, we could typically expect to be off by ± 33.85%. |
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2) You are estimating the cost ($K) of optical sensors based on the resolution of the sensor (i.e. how small of an object it can detect). Using the preliminary calculations from a data set of 8 sensors, determine the equation of the line. (Round your intermediate calculations to 3 decimal places) ∑Y = 2515 ∑X = 30 ∑XY = 6857.5 ∑X2 = 161 [removed][removed] | | | | | [removed]Cost = - 53.067 + 115.374 (Resolution) | [removed]Cost = 513.376 + (- 53.067) (Resolution) | [removed]Cost = 115.374 + (-53.067) (Resolution) | [removed]Cost = - 53.067 + 513.376 (Resolution) |
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3) You are trying to determine the statistical significance of an equation. Given the following information, test the slope of the equation at the 95% level of confidence. Select the correct answer out of each pair of choices. Cost = - 76.25 + 114.82 (Range) n = 9 Sb1 = 17.669 [removed][removed] | | | | | [removed]The tp is 1.895 | [removed]The tp is 2.365 | [removed]The tc is 4.315 | [removed]The tc is 6.498 | [removed]We would reject the null hypothesis | [removed]We would fail to reject the null hypothesis | [removed]We would consider using the equation | [removed]We would not use the equation |
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4) You have calculated the following power model and associated unit space values: You would select the: [removed][removed] | | | | | | | [removed]Power equation because it has a higher standard error than the linear model. | [removed]Power equation because it has a lower standard error than the linear model. | [removed]Linear equation because it has a higher standard error than the power model. | [removed]Linear equation because it has a lower standard error than the power model. |
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5) A coworker is considering the use of a log linear (power) model using weight to estimate the cost of a utility vehicle. They have performed the following calculations in log space using natural logarithms. Select the corresponding unit space form of this power model equation. Log Space b1 = 1.268074 b0 = 0.062153 [removed][removed] | | | | | [removed]Cost = 1.268074 + 0.062153 (Weight) | [removed]Cost = 0.062153 + 1.268074 (Weight) | [removed]Cost = 1.064125 (Weight) 1.268074 | [removed]Cost = 0.062153 (Weight) 1.268074 |
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