Big Data - Exam II

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Big Data - Exam II
2013-09-28 15:57:43
Modeling Analysis Sensitivity

Modeling & Analysis - Sensitivity Analysis
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  1. sensitivity analysis
    attempts to assess the impact of a change in the input data or parameters on the proposed solution (i.e., the result variable)
  2. sensitivity analysis
    analysis approach used to determine how the output is changing based on how I change the input
  3. what-if analysis
    assesses solutions based on changes in variables or assumptions (scenario analysis)
  4. goal seeking analysis
    an analysis approach that determines how the input is changing based on what I want the output to be
  5. automatic & trial-and-error
    two types of sensitivity analyses
  6. automatic sensitivity analysis
    reports the range within which a certain input variable or parameter value can vary without having any significant impact on the proposed solution - usually limited to one change at a time, and only for certain variables, but is able to establish ranges and limits very fast
  7. trial-and-error sensitivity analysis
    analysis used to determine the impact of changes in any variable or in several variables - changes are made in input data and the problem is solved again and repeated to find better and better solutions
  8. what-if analysis & goal seeking
    two approaches to trial-and-error sensitivity analysis
  9. what-if analysis
    analysis that determines what will happen to the solution if an input variable, an assumption, or a parameter value is changed - is common in expert systems
  10. goal seeking
    calculates the values of the inputs necessary to achieve a desired level of an output - a backward solution approach
  11. break-even point
    the value of the decision variables that generate zero profit
  12. decision analysis
    approach used for modeling decision situations that involve a finite and usually not too large number of alternatives - where the alternatives are listed in a table or a graph, with their forecasted contributions to the goal(s) and the probability of obtaining the contribution - can be evaluated to select the best alternative
  13. decision tables or decision trees
    single-goal situations can be modeled with _____.
  14. decision tables
    organize information and knowledge in a systematic, tabular manner to prepare it for analysis - multiple criteria decision analysis with one goal in mind
  15. optimistic approach
    method for handling uncertainty that assumes that the best possible outcome of each alternative will occur and then selects the best of the best
  16. pessimistic approach
    method for handling uncertainty that assumes that the worst possible outcome for each alternative will occur and selects the best of these
  17. expected value
    in a decision table, computing _____  is done by multiplying the results (i.e., outcomes) by their respective probabilities and adding them.
  18. decision tree
    multiple criteria decision approach that shows the relationships of the problem graphically and can handle complex situations in a compact form (but can be combersome if there are many alternatitives)
  19. multiple goals
    a decision situation in which alternatives are evaluated with several, sometimes conflicting, goals
  20. analytic hierarchy process (AHP)
    modeling structure for representing multicriteria (multiple goals, multiple objectives) problems - with sets of criteria and alternatives (choices) - often assigning distributed weights to different ranked criterion
  21. analytical (optimization) techniques
    blind searching
    heuristic searching
    formal search approach methods used in the choice phase of problem solving
  22. analytical search techniques
    use mathematical formulas to derive an optimal solution directly or to predict a certain result - used mainly for solving structured problems
  23. algorithms
    a step-by-step search process for obtaining an optimal solution (or more than one) - with improvements made as needed until no further improvement is possible (ex: web searches)
  24. blind search
    consists of searches that are not guided, which include complete enumeration and incomplete or partial searches
  25. complete enumeration
    a type of blind search in which all the alternatives are considered and therefore an optimal solution is discovered
  26. incomplete or partial search
    a type of blind search which continues until a good-enough solution (or best among alternatives checked) is found, and is a form of suboptimization
  27. blind
    ____ searches are not pratical for solving very large problems because too many solutions must be examined before an optimal solution is found.
  28. heuristics
    the informal judgmental knowledge of an application area that constitute the rules of good judgment in the field
  29. heuristic programming
    the process of using heuristics in problem solving
  30. simulation
    the appearance of reality - a technique for conducting experiments with a computer on a model of a management system - to assist in dealing with the complexity of reality
  31. models
    ____ generally represent reality, whereas ____ typically imitates it
  32. simulation
    ____ is normally used only when a problem is too complex to be treated using numerical optimization techniques.