Data Analysis Archives

How to Automatically Display Residual Values in Regression Analysis Using Excel

Regression Tutorial using Excel / By Kanda Data / April 25, 2025

Residual values play an important role in linear regression analysis. These residuals are used for OLS assumption tests, such as normality tests and heteroskedasticity tests. For instance, one of the key assumptions in linear regression analysis is that the residuals are normally distributed. Therefore, we need to first calculate the residual values before proceeding with …

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Spearman Rank Correlation Analysis | Practical Test on the Relationship Between Education Level and Performance Level

Correlation Test / By Kanda Data / March 9, 2025

In statistics, correlation tests are frequently used by researchers to examine associations. The purpose of conducting a correlation test is to determine the relationship between two observed variables. However, many people still ask me about one specific correlation test for variables measured on an ordinal scale.

How to Perform Multiple Linear Regression Analysis in Excel: Data Analysis Tools

Multiple Linear Regression / By Kanda Data / January 12, 2025

Multiple linear regression analysis is a method used when a researcher aims to estimate the effect of independent variables on a dependent variable. In multiple linear regression, the number of independent variables must be at least two.

How to Find the Standard Deviation of Sample Data in Excel

Statistics / By Kanda Data / January 5, 2025

One of the metrics in statistics is the standard deviation. When conducting research, the standard deviation is crucial for describing the data you have obtained. It illustrates the dispersion of the data relative to the mean.

How to Perform Residual Normality Analysis in Linear Regression Using R Studio and Interpret the Results

Data Analysis in R / By Kanda Data / November 11, 2024

Residual normality testing is a key assumption check in linear regression analysis using the Ordinary Least Squares (OLS) method. One essential requirement of linear regression is that the residuals should follow a normal distribution. In this article, Kanda Data shares a tutorial on how to perform residual normality analysis in linear regression using R Studio, …

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