Monthly Archives: April, 2023

How to Test Heteroscedasticity in Linear Regression and Interpretation in R (Part 3)

Kanda Data - April 30, 2023 0

One of the assumptions required in Ordinary Least Squares (OLS) linear regression is that the variance of the residuals is constant. This assumption is...

How to Analyze Multicollinearity in Linear Regression and its Interpretation in R (Part 2)

Kanda Data - April 17, 2023 0

Non-multicollinearity is one of the assumptions required in the ordinary least square (OLS) method of linear regression analysis. Non-multicollinearity assumption implies that there is...

How to Analyze Multiple Linear Regression and Interpretation in R (Part 1)

Kanda Data - April 11, 2023 2

Multiple linear regression analysis has been widely used by researchers to analyze the influence of independent variables on dependent variables. There are many tools...

How to Transform Natural Logarithm (ln) and Reverse (anti-Ln) in Excel

Kanda Data - April 6, 2023 0

Researchers often transform data to convert original data into another form to meet certain assumptions. Researchers can do several forms of data transformation. Natural...

Step-by-Step Tutorial: Finding Predicted and Residual Values in Linear Regression with Excel

Kanda Data - April 3, 2023 0

In linear regression analysis, residual values play an important role in supporting the main analysis. Residual values are the difference between actual values and...