Search results
Results from the WOW.Com Content Network
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 ...
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 ...
Trend analysis is the widespread practice of collecting information and attempting to spot a pattern. In some fields of study, the term has more formally defined meanings. [1] [2] [3]
Forecasting can be described as predicting what the future will look like, whereas planning predicts what the future should look like. [6] There is no single right forecasting method to use. Selection of a method should be based on your objectives and your conditions (data etc.). [9] A good way to find a method is by visiting a selection tree.
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.
This method, developed by Sohail Inayatullah, is one of the newest developments in Futurology. Causal layered analysis focuses on "opening up" the present and past to create alternative futures rather than on developing a picture of a particular future. It is concerned with the vertical dimension of futures studies, with the layers of analysis.
Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. [1] [2] Exploratory causal analysis (ECA), also known as data causality or causal discovery [3] is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions.
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.