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The Basics of Multivariate Regressions in Excel
Batova, Tatiana Technical Note BC-0311 / Published August 26, 2024 / 4 pages. Collection: Darden School of Business
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This technical note provides a comprehensive guide to conducting multivariate linear regressions using Excel. It covers essential concepts such as setting up the regression model, selecting variables, and interpreting the results. Key outputs from Excel’s regression tool, including coefficients, standard errors, t-stats, p-values, and R-squared, are explained in detail. Additionally, the document highlights the limitations of Excel for advanced statistical analysis. The technical note uses example data from the case “Flying Around Real Estate Development: Persuading with Data Visualizations” (UVA-BC-0285); the case itself is optional for those who wish to read more.




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  • Overview

    This technical note provides a comprehensive guide to conducting multivariate linear regressions using Excel. It covers essential concepts such as setting up the regression model, selecting variables, and interpreting the results. Key outputs from Excel’s regression tool, including coefficients, standard errors, t-stats, p-values, and R-squared, are explained in detail. Additionally, the document highlights the limitations of Excel for advanced statistical analysis. The technical note uses example data from the case “Flying Around Real Estate Development: Persuading with Data Visualizations” (UVA-BC-0285); the case itself is optional for those who wish to read more.

  • Learning Objectives