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Criticality Index
Criticality index is mainly used in risk analysis. The Criticality Index of an activity (task) can be expressed as a ratio (between 0 and 1) but is more often expressed as a percentage. During a (e.g. Monte Carlo) simulation tasks can join or leave the critical path for any given iteration. The Criticality Index expresses how often a particular task was on the Critical Path during the analysis. Tasks with a high Criticality Index are more likely to cause delay to the project as they are more likely to be on the Critical Path. If a task does not exist for some iterations (e.g. it is probabilistic) then it is marked as not being critical. For example, a task that existed for 50% of the iterations and was critical 50% of the time it existed would have a Criticality Index of 25%. Benefits The Criticality Index allows you to identify tasks that are likely to cause delays to the project.{{cite book , vauthors=Virine L, Trumper M, title = Project Risk Analysis Made Ridiculously Simple , ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Spearman's Rank Correlation Coefficient
In statistics, Spearman's rank correlation coefficient or Spearman's ''ρ'', named after Charles Spearman and often denoted by the Greek letter \rho (rho) or as r_s, is a nonparametric measure of rank correlation ( statistical dependence between the rankings of two variables). It assesses how well the relationship between two variables can be described using a monotonic function. The Spearman correlation between two variables is equal to the Pearson correlation between the rank values of those two variables; while Pearson's correlation assesses linear relationships, Spearman's correlation assesses monotonic relationships (whether linear or not). If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other. Intuitively, the Spearman correlation between two variables will be high when observations have a similar (or identical for a correlation of 1) rank (i.e. relative position la ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pearson Product-moment Correlation Coefficient
In statistics, the Pearson correlation coefficient (PCC, pronounced ) ― also known as Pearson's ''r'', the Pearson product-moment correlation coefficient (PPMCC), the bivariate correlation, or colloquially simply as the correlation coefficient ― is a measure of linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations. As a simple example, one would expect the age and height of a sample of teenagers from a high school to have a Pearson correlation coefficient significantly greater than 0, but less than 1 (as 1 would represent an unrealistically perfect correlation). Naming and history It was developed by Ka ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
