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Regression Analysis and Forecasting 3.0 by Business SpreadsheetsDownload

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License Shareware / $19
Downloads 153
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File size 167.0 K
Date added 28-Apr-2015
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Editor's review:

This tool provides regression analysis and financial forecast templates built on Excel.

This tool comes with multiple regression analysis and forecasting templates for the MS Excel program. Through the use of these templates, you are able to identify causal and predictive relationships within a series of datasets. The results are produced with high statistical confidence and thus produce reliable results. The multiple regression process employs a set of established statistical measures that ensure the results are valid. The tool forecasts by providing analysis by several methodologies. These methodologies ensure that forecasting for independent variables for predicting and forecasting with the predictive analytics and regression equation is easily possible. Explanatory text is provided that facilitates interpretation and simplifies the identification of appropriate predictive relationships. The workflow is simple and intuitive. It helps to develop robust predictions easily and quickly.

The tool is flexible enough to let you do regression and predictive analyses on a range of data types. These include business and financial data, time series and scientific data. Common business applications for predictive analytics via multivariate regression include real estate or market valuation and sales forecasting and best are developed quite easily. Best combination of variables that fits the regression and lets you get maximum accuracy and persistence of predictions are used. You do not need statistical skills to be able to interpret the results appropriately. The utility carries out statistical tests for significance, autocorrelation and multi-collinearity calculations. These are calculated, displayed and explained so that they can be easily interpreted and acted on. This tool uses options like 3rd polynomial, 2nd polynomial, exponential or linear trend lines on independent variables. Independent variable forecast input can be left empty to use external forecast data or alternative assumptions.


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