Decision Trees B. Markov Analysis C

Decision Trees B. Markov Analysis C 1

Expected values are computed by multiplying: a. Q3. Linear programming consists of experimenting on a model of a system. Q4. Models can be categorized as static, powerful, or both. Q5. A DSS is designed to determine what will be; an MIS was created to report what was. Q6. Sensitivity analysis attempts to assess the impact of a change in the input data on the proposed solution.

Q7. Static models signify developments or situations as time passes. Q8. Simulation consists of experimenting on a style of a functional system. Q9. Decision-making under certainty is always easy to solve. Q10. Spreadsheet software such as Microsoft Excel is with the capacity of carrying out both what-if and goal seeking evaluation. Q11. The decision-maker’s attitude toward risk can change the results of a predicament regarding risk. Q12. Which model is designed to find a very good solution from a big number of possible alternatives utilizing a step-by-step process? Decision trees b. Markov analysis c. Linear programming d. Heuristic development e. Q13. Influence diagrams can be designed with varying examples of fine detail. Q14. Decision dining tables work best for multiple-goal problems.

Q15. Goal-seeking analysis is effective in identifying the known level of input needed to achieve a desired result. Q16. The types of decision-making situations that may require analysis (in order of increasing complexity) are certainty, risk, and uncertainty. Q17. The highest level of detail supported with a data warehouse is its grain.

Q18. Information is organized data. Q19. Knowledge contains data items and/or information processed and organized to convey understanding, experience, accumulated learning, and expertise as they connect with a current activity or problem. Q20. There is a temporal quality to data warehouses. Q21. Within a data warehouse, data are structured by: a. Q22. In lots of ways, establishing a data warehouse is similar to setting up a separate data source for DSS. Q23. Business dashboards provide real-time views of data a. Q24. Sophisticated data mining systems can automatically discover knowledge in data warehouses by finding relationships that are concealed within the info. Q25. Data, information, and knowledge are the same thing essentially.

Q26. When the office access data from the marketing division they are employing external data since it comes from a source outside their section. Q27. A star schema starts with a central aspect table that is associated with one or more fact desks. Q28. Data quality is important because the quality can be suffering from it of organizational decisions. Q29. Data quality and data integrity is essentially the same thing. Q30. Both most common data warehouse architectures are three-tiered and four-tiered. Q31. The relational model is one of the best database models.

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Q32. Intrinsic data quality identifies the simple interpretability or knowledge of data. Q33. Integrated CASE tools are only used in the implementation and design stage. Q34. Identifying the viability of an basic idea is completed within the analysis phase. Q35. Staffing the DSS project is completed after the analysis has been completed. Q36. The Lewin-Schein change theory is only useful for introducing departmental change to a business.

Q37. Prototyping is generally known as iterative design. Q38. Prototyping is the single best DSS development technique. Q39. The waterfall development approach essentially works like water, it only downward flows. Q40. User-developed DSS and end-user processing are the same thing essentially. Q41. Organizations shall typically only use one DSS generator as a means to regulate costs.