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Home/Residuals

Tag: Residuals

Assumptions of Linear Regression

Assumptions of Multiple Linear Regression on Time Series Data

By Kanda Data / Date Jul 25.2024

Multiple linear regression is a statistical analysis technique used to model the relationship between one dependent variable and two or more independent variables. The multiple linear regression model is used to predict the value of the dependent variable based on the estimated values of the independent variables.

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How to Find Residuals Using the Data Analysis ToolPak in Excel

By Kanda Data / Date Jul 08.2024 / Category Econometrics

Residuals are the differences between the observed values of the dependent variable and the predicted values from the dependent variable. Residuals are an important measure in inferential analysis, particularly in regression analysis. Given the importance of residuals, we will discuss how to find residual values using Excel.

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Multiple Linear Regression

Understanding the Difference between Residual and Error in Regression Analysis

By Kanda Data / Date Apr 05.2024

When expressing a linear regression equation, the terms residual or error often appear at the end of the equation. But what exactly do residual and error mean? And what is the fundamental difference between the two?

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