Compatible with all versions of Excel for Windows and Excel for Mac 20. Forecasting can be undertaken based on linear or exponential forecasts of independent variables or left blank for input of external calculated data. When there is a single input variable (x), the method is referred to as simple linear regression. More specifically, that y can be calculated from a linear combination of the input variables (x). a model that assumes a linear relationship between the input variables (x) and the single output variable (y). Quick forecasting process with options to employ 3rd order polynomial, 2nd order polynomial, exponential or linear trend lines on independent variables.Īdvanced statistical tests are undertaken to confirm the validity of predictive relationships identified in the input data. Linear regression is a linear model, e.g. Tests for statistical significance, autocorrelation, and multicollinearity. Multiple and individual regression of independent variables. User-friendly results display for the non-statistician.
The Excel regression analysis solution provides much more functionality and more intuitive results display than the standard regression analysis provided within Excel via the Analysis Toolpak add-in.Įase and flexibility of input, with embedded help prompts. Ensure your data is in two columns (or rows) in an Excel workbook. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies. How-to guide: regression analysis in Excel (Office 365). While the regression analysis utilizes a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use.
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The Excel Regression Analysis and Forecasting model provides a reliable basis for identifying value drivers and forecasting business and scientific data.
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