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  2. Causal layered analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_layered_analysis

    Causal layered analysis (CLA) is a theory and method that seeks to integrate empiricist, interpretive, critical, and action learning modes of research. In this method, forecasts, the meanings individuals give to these forecasts, the critical assumptions used, the narratives these are based on, and the actions and interventions that result are ...

  3. Causal analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_analysis

    Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...

  4. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    In statistics, trend analysis often refers to techniques for extracting an underlying pattern of behavior in a time series which would otherwise be partly or nearly completely hidden by noise. If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis , as described in Trend estimation .

  5. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.

  6. Cash flow forecasting - Wikipedia

    en.wikipedia.org/wiki/Cash_flow_forecasting

    Cash flow forecasting is the process of obtaining an estimate of a company's future cash levels, and its financial position more generally. [1] A cash flow forecast is a key financial management tool, both for large corporates, and for smaller entrepreneurial businesses. The forecast is typically based on anticipated payments and receivables.

  7. Bayesian structural time series - Wikipedia

    en.wikipedia.org/wiki/Bayesian_structural_time...

    Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data.

  8. Pricing science - Wikipedia

    en.wikipedia.org/wiki/Pricing_science

    Forecasting methods generally fall into the class of methods known as time series methods, primarily exponential smoothing, or causal methods, where price is taken to be (one of) the causal factors. In pricing science applications, it is necessary to produce forecasts of demand at the level of granularity at which pricing decisions are made.

  9. Futures techniques - Wikipedia

    en.wikipedia.org/wiki/Futures_techniques

    Futures techniques used in the multi-disciplinary field of futurology by futurists in Americas and Australasia, and futurology by futurologists in EU, include a diverse range of forecasting methods, including anticipatory thinking, backcasting, simulation, and visioning. Some of the anticipatory methods include, the delphi method, causal ...