Constraints final shadow constraint allowable

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Constraints Final Shadow Constraint Allowable Allowable Cell Name Value Price R.H. Side Increase Decrease $B$17 Labor Hours Used 40 56.66666667 40 15 15 Final value of constrained value The amount the outcome would change if this constraint were increased or decreased by one unit. Max/min allowed value for constraint How much the constrained value could change while holding the shadow price constant.
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Time Series Data Components Components Trend: The overall direction of the data Seasonality: Repetitive patterns at defined time intervals Cycles: Consistent periods of over/under-prediction where time interval and magnitude of peak/valley is inconsistent Noise: Random deviations from the pattern for given observations Which of these can we control for using linear regression? How? Trend – with trend variable Seasonality – using months/season/weeks (anything predictable). Cyclicality – difficult to predict using LR
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Overview of SQL SELECT Structure SELECT … FROM … [LEFT/RIGHT/INNER] JOIN … ON … = … WHERE … (operator) … GROUP BY … HAVING … (operator) … ORDER BY …
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  • Fall '08
  • Staff
  • Regression Analysis, upper bound, sensitivity report, logistic regression equation, log odds ratio

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