Expected value is the weighted average of all the possible values of a random variable, with the probabilities of each of the values used as the weights. The expected value is the mean value, also known as the average value. Expected value analysis does not yield an immediate financial estimate of the consequences of possible prediction errors.
Regression analysis is a method of forecasting, using trend analysis. However, it does not yield an immediate financial estimate of the consequences of possible prediction errors.
Learning curves describe the fact that the more experience people have with something, the more efficient they become in doing that task. Higher costs per unit early in production are part of start-up costs. It is commonly accepted that new products and production processes experience a period of low productivity followed by increased productivity. However, learning curve analysis does not provide an immediate financial estimate of the consequences of possible prediction errors.
Sensitivity analysis can be used to determine how cash flows can be expected to vary with changes in the underlying assumptions. Using expected cash flows, the NPV, IRR, and PI of the project are determined. Then, the key assumptions that were used in making the original expected cash flow projections are identified. One assumption at a time is then changed, leaving the other assumptions unchanged, and the NPV, IRR and PI are recalculated to determine what effect changing one assumption would have on those measures.
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