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  2. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis, as described in Trend estimation. If the trends have other shapes than linear, trend testing can be done by non-parametric methods, e.g. Mann-Kendall test, which is a version of Kendall rank correlation coefficient.

  3. 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. Prediction is a similar but more general term.

  4. Futures techniques - Wikipedia

    en.wikipedia.org/wiki/Futures_techniques

    Trend analysis is one of the most often used methods in forecasting. It aims to observe and register the past performance of a certain factor and project it into the future. It involves analysis of two groups of trends: quantitative, mainly based on statistical data, and qualitative, these are at large concerned with social, institutional ...

  5. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered tends to increase or decrease over time or is influenced by changes in an external factor.

  6. Futures studies - Wikipedia

    en.wikipedia.org/wiki/Futures_studies

    Futures studies, futures research, futurism research, futurism, or futurology is the systematic, interdisciplinary and holistic study of social/technological advancement, and other environmental trends; often for the purpose of exploring how people will live and work in the future.

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    ARIMA univariate and multivariate models can be used in forecasting a company's future cash flows, with its equations and calculations based on the past values of certain factors contributing to cash flows. Using time-series analysis, the values of these factors can be analyzed and extrapolated to predict the future cash flows for a company.