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Home/Archive for: September 2023

Month: September 2023

Multiple Linear Regression

How to Detect Multicollinearity in Multiple Linear Regression Equations Using the OLS Method

By Kanda Data / Date Sep 15.2023

Multicollinearity testing is one of the assumptions in the least squares method of multiple linear regression. This test is conducted to determine whether there is a strong correlation between independent variables.

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Econometrics

Definition and Purpose of Determining Residual Values in Linear Regression Analysis

By Kanda Data / Date Sep 12.2023

In linear regression analysis, residual values play a crucial role. The residual value is the difference between the actual and predicted Y values. The actual Y value can be obtained from observations or samples of the dependent variable.

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Multiple Linear Regression

How to Interpret Dummy Variables in Ordinary Least Squares Linear Regression Analysis

By Kanda Data / Date Sep 10.2023

Dummy variables, which have non-parametric measurement scales, can be used in specifying linear regression equations. The linear regression equation I’m referring to here is the ordinary least squares (OLS) method. As we already know, most variables are measured on interval and ratio scales in ordinary least squares linear regression equations.

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Econometrics

Coefficient of Determination and How to Interpret it in Linear Regression Analysis

By Kanda Data / Date Sep 05.2023

The coefficient of determination in linear regression analysis is crucial in understanding how well the independent variables explain the dependent variable. In linear regression analysis, the coefficient of determination can come in two forms: the coefficient of determination (R square) and the adjusted coefficient of determination (Adjusted R Square).

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Econometrics

Natural Logarithm Transformation in Cobb-Douglas Regression

By Kanda Data / Date Sep 04.2023

The Cobb-Douglas production function is often referred to as an exponential production function. Researchers have widely used this Cobb-Douglas production function to empirically analyze various phenomena in production functions.

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Correlation Test

How to Analyze Correlation of Variables Measured Using Likert Scale

By Kanda Data / Date Sep 01.2023

Correlation analysis is the chosen method when conducting research to understand the relationship between variables. Correlation analysis in statistics can take the form of partial correlation analysis and multiple correlation analysis.

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Categories

  • Article Publication
  • Assumptions of Linear Regression
  • Comparison Test
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