Xem 1-7 trên 7 kết quả Plotting a point
  • This book is dedicated to the many colleagues and numerous students who moulded me into a better teacher.In particular my first Head of Department, Gerry Astell, who taught me never to teach something that I knew I would later retract. False simplicity is never helpful to the student in the long run; it just makes a poor teacher’s life easier for a moment.

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  • Why are we interested in solving simultaneous equations? We often have to find a point which satisfies more than one equation simultaneously, for example when finding equilibrium price and quantity given supply and demand functions.  To be an equilibrium, the point (Q; P) must lie on both the supply and demand curves.  Now both supply and demand curves can be plotted on the same diagram and the point(s) of intersection will be the equilibrium (equilibria)

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  • Chapter 4: Metrics to Identify Project Improvement Opportunities In the last chapter we discussed Kiviatt Charts and Box & Whisker Plots. These are two tools that can be used to display PD and PP data in our search for process-wide and practice-wide improvement opportunities. This would typically be the starting point for identifying major areas where improvement opportunities should be focused.

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  • 1) Introduction The estimates of the regression parameters are influenced by a few extreme observations. The residual plot may let us pick out, which the individual data points are high or low. We may use the residual plot to find the outlier, which are inadequately captured by the regression model itself.

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  • It is a curve in which unit load or stress is plotted against unit elongation, technically known as strain. O– A represents the stress is directly proportional to strain, and point A is known proportional limit. Point B represents elastic limit beyond which the material will not return to its original shape when unloaded but will retain a permanent deformation called permanent set.

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  • Calculating sensitivity and specificity requires selection of a decision value for the test to define the threshold value at or above which the test is considered "positive." For any given test, as this cut point is moved to improve sensitivity, specificity typically falls and vice versa. This dynamic tradeoff between more accurate identification of subjects with disease versus those without disease is often displayed graphically as a receiver operating characteristic (ROC) curve (Fig. 3-1). An ROC curve plots sensitivity (y-axis) versus 1 – specificity (x-axis).

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  • More important is the scatter plot of data points, each representing a microfinance institution. Many points are above the threshold for profitability, and many are on the left of the graph, indicating low reliance on soft (subsidized) funds. This is the hope of commercial microfinance. But note too that an ample number of institutions are above the threshold and to the right, funded by social investors of various stripes. The solid circles represent institutions with for-profit status, while the empty circles are non-profits.

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