Code : 8612-3
Products Description : Multiple Regression Analysis and Forecasting
The Excel Multiple Regression Analysis and Forecasting template enables the confident identification of value drivers and forecasting of business plan or scientific data. The multiple regression process utilizes commonly employed statistical measures to test the validity of the analysis and results are summarized in textual form to be easily understood and interpreted.Once statistically robust predictive relationships have been identified by the regression analysis, forecasting can be quickly accomplished based on a range of available methodologies and accompanying statistical strength. An intuitive stepwise work flow enables to develop strong forecasts for analytical and business projects in a timely manner.
The Multiple Regression Analysis and Forecasting template provides simple and flexible input with integrated help icons to facilitate utilization. Results and statistics are explained in a user friendly manner to be understood by users of all levels of expertize without requiring experience in statistics.
The Multiple regression analysis and forecasting template provides much more functionality than the Excel Analysis Toolpak add-in such as individual regression of all independent variables, the actual level of confidence for the results, and tests of for autocorrelation and multicollinearity.
The forecasting process provides options to employ 3rd polynomial, 2nd polynomial, exponential or linear trend lines on independent variables as well as the option to override independent variable forecast data with external analysis or in-house forecasts.
The Multiple Regression Analysis and Forecasting template is compatible with Excel 97-2013 for Windows and Excel 2011 or 2004 for Mac as a cross platform regression prediction and forecasting solution.
Product Details : Multiple Regression Analysis and Forecasting
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Keyword
multiple, regression, forecasting, analysis, excel, business, planning, statistical, multicolinerity, autocorrelation, correlation, r-squared, value, drivers, identification
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