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Producing statistically sound value driver identification for forecasting data
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The Multiple Regression Analysis and Forecasting model provides a solid basis for identifying value drivers and forecasting business plan data. While it utilises a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use. Once relationships have been identified, forecasting can be accomplished based on a range of available methodologies. The intuitive step-by-step usage flow enables you to develop strong forecasts for your projects in a timely manner. The key features of the Multiple Regression Analysis and Forecasting model include: Ease and flexibility of input, with embedded help prompts; User-friendly results display for the 'Non-statistician'; Multiple and Individual Regression of independent variables; Tests for statistical significance, auto-correlation, and multi-colinearity; and Quick forecasting process with options to employ 3rd polynomial, 2nd polynomial, exponential or linear trend lines on independent variables.
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Buy ($14.00) / Download (162.1 KB)
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Excel, forecasting, multiple, regression, template, spreadsheet, business, planning, plan, proposal, statistical, testing, multicolinearity, auto, correlation, Durbin-Watson, Pearson, Coefficient, value, drivers, identification, analysis
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Avg. User Rating |
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2%
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1%
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| 103 / 3 (total / last month) |
| 08-12-2005 16:29:48 GMT |
| 01-01-2005 |
| English |
| Win95, Win98, WinME, WinNT 3.x, WinNT 4.x, Windows2000, WinXP |
| Requires Microsoft Excel 97 or higher |
| Install and Uninstall |
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