hw2 - The line looks like reasonable, since the correlation...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon
ENGRD2700 Fall 2008 HWK#2 1 (a)The quantile plot is: 1.0 0.8 0.6 0.4 0.2 0.0 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 Quantile Sorted OP Scatterplot of Sorted OP vs Quantile
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
(b) 3.0 2.7 2.4 2.1 1.8 1.5 1.2 Op NoOp Data Dotplot of Op, NoOp NoOp Op 3.0 2.5 2.0 1.5 1.0 Data Boxplot of Op, NoOp
Background image of page 2
( c) 3.0 2.5 2.0 1.5 1.0 3.0 2.5 2.0 1.5 1.0 NoOp OP Sorted OP * Sorted NoOp C8 * C9 Variable Scatterplot of Sorted OP vs Sorted NoOp, C8 vs C9 We can infer that the quantile of Op is always larger than NoOp, since the Q-Q plot lies strictly above the 45 degree straight line. (d) We do the interpolation for the observations of Operations, then we get the Q-Q plot:
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 2.8 2.6 2.4 2.2 2.0 1.8 NoOp quantile New Op quantile Scatterplot of New Op quantile vs NoOp quantile 2(a) The regression line is : Interval=33.97+10.36*Duration 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 100 90 80 70 60 50 40 Duration Interval Scatterplot of Interval vs Duration
Background image of page 4
Correlations: Duration, Interval Pearson correlation of Duration and Interval = 0.877 P-Value = 0.000
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Background image of page 6
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: The line looks like reasonable, since the correlation of the two variables are 0.877>0, and from the regression equation, we see the Interval increases as the Duration increases. (c) Descriptive Statistics: Error Variable Minimum Q1 Median Q3 Maximum Error 0.000 5.000 10.000 16.000 29.000 Descriptive Statistics: NewError Variable Minimum Q1 Median Q3 Maximum NewError 0.000 2.000 4.000 7.000 25.000 Descriptive Statistics: Error Pred Variable Minimum Q1 Median Q3 Maximum Error Pred 0.238 1.624 4.410 7.340 16.806 Error Pred NewError Error 30 25 20 15 10 5 Data Boxplot of Error, NewError, Error Pred (d) The (iii) is preferred, because the difference of extremes of this method is narrower than the other two predictions. We can also observe that the maximum error of Method (iii) is the smallest among the three candidates, which is what we desire....
View Full Document

This note was uploaded on 09/26/2008 for the course ENGRD 2700 taught by Professor Staff during the Fall '05 term at Cornell University (Engineering School).

Page1 / 6

hw2 - The line looks like reasonable, since the correlation...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online