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Home/Econometrics

Category: Econometrics

How to Create Dummy Variables in Multiple Linear Regression Analysis

By Kanda Data / Date Jul 31.2025 / Category Econometrics

For those of you conducting multiple linear regression analysis, have you ever used dummy variables? These variables are very useful when we want to include categorical variables in a multiple linear regression equation.

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How to Detect Normally Distributed Data in Linear Regression Analysis

By Kanda Data / Date Jul 28.2025 / Category Econometrics

When you conduct data analysis using linear regression, there are several assumptions that must be met. We need to fulfill these assumptions to ensure that the estimation results are consistent and unbiased.

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Natural Logarithm Data Transformation to Improve Data Normality, Is It True?

By Kanda Data / Date Jul 09.2025 / Category Econometrics

In parametric statistical analysis, several assumptions must be met, one of which is the assumption that data should be normally distributed. However, in practice, the data obtained from research does not always follow a normal distribution based on statistical tests. Therefore, some researchers attempt to adjust the distribution of data to make it more closely resemble a normal distribution. One common method is data transformation. Among various types of data transformations, the natural logarithm transformation is one of the most commonly used.

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Regression Analysis on Non-Parametric Dependent Variables: Is It Possible?

By Kanda Data / Date Aug 28.2024 / Category Econometrics

In multiple linear regression analysis, the measurement scale of the dependent variable is typically parametric. However, can multiple linear regression analysis be applied to a dependent variable measured on a nominal (non-parametric) scale?

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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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Econometrics

The Difference Between Simultaneous Equation System Model and Linear Regression Equation

By Kanda Data / Date Mar 29.2024

We might all be familiar with linear regression equations, but how many of us have delved deeper into the simultaneous equation system model? It’s worth noting that the simultaneous equation system model is far more complex than linear regression equations.

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Econometrics

Can Data Transformation Be Done More Than Once?

By Kanda Data / Date Oct 11.2023

For those of us accustomed to conducting research, understanding how to analyze data is a crucial skill to master. In the process, when we are processing data, we are sometimes faced with the choice of data transformation.

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Econometrics

How to Interpret the Coefficient of Determination (R-squared) in Linear Regression Analysis

By Kanda Data / Date Sep 28.2023

The coefficient of determination (R-squared) is a statistical metric used in linear regression analysis to measure how well independent variables explain the dependent variable. It indicates the quality of the linear regression model created in a research study.

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Categories

  • Article Publication
  • Assumptions of Linear Regression
  • Comparison Test
  • Correlation Test
  • Data Analysis in R
  • Econometrics
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  • Multiple Linear Regression
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  • Regression Tutorial using Excel
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