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A what if chart (Whif chart, WHIF analysis, etc.) is a visual tool for modeling the outcome of a combination of different factors.The table can represent actual results or predicted outcome based on combinations of parameters.
This can also be called what-if analysis or backsolving. It can either be attempted through trial and improvement or more logical means. Basic goal seeking functionality is built into most modern spreadsheet packages such as Microsoft Excel. According to O'Brien and Marakas, [1] optimization analysis is a more complex extension of goal-seeking ...
For example, a comparison of a spreadsheet cost construction model run using traditional "what if" scenarios, and then running the comparison again with Monte Carlo simulation and triangular probability distributions shows that the Monte Carlo analysis has a narrower range than the "what if" analysis.
The structured what-if technique (SWIFT) is a prospective hazards analysis method that uses structured brainstorming with guidewords and prompts to identify risks, [1] with the aim of being quicker than more intensive methods like failure mode and effects analysis (FMEA). [2] [3] It is used in various settings, including healthcare. [1] [2] [3] [4]
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
What-if analysis. Add languages. Add links. Article; Talk; English. ... Download QR code; Print/export Download as PDF; Printable version; In other projects
Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11]
In Bayesian statistics, the model is extended by adding a probability distribution over the parameter space . A statistical model can sometimes distinguish two sets of probability distributions. The first set Q = { F θ : θ ∈ Θ } {\displaystyle {\mathcal {Q}}=\{F_{\theta }:\theta \in \Theta \}} is the set of models considered for inference.