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Natural Logarithmic Data Transformation using Excel | Simple Steps

Excel Tutorial for Statistics / By Kanda Data / April 16, 2025

When conducting analysis using parametric methods, it is generally required that the data follow a normal distribution. However, in reality, data collected from the field often do not meet this expectation. Tests such as the Shapiro-Wilk test or the Kolmogorov-Smirnov test may show that the data are not normally distributed. This situation often leads researchers …

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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 Calculate Tolerance Value and Variance Inflation Factor (VIF)

Assumptions of Linear Regression / By Kanda Data / February 10, 2025

The tolerance value and Variance Inflation Factor (VIF) are important metrics that you can use to detect multicollinearity among independent variables. If we recall the basic theory, multicollinearity testing is an assumption test in the Ordinary Least Squares (OLS) regression method, which aims to ensure that there is no strong correlation between independent variables.

How to Calculate the Variance Inflation Factor (VIF) in a Multicollinearity Test for Regression

Assumptions of Linear Regression / By Kanda Data / January 29, 2025

In linear regression analysis, to obtain the best linear unbiased estimator, you need to perform a series of assumption tests. One of the assumption tests required in linear regression is the multicollinearity test.

How to Determine Alpha Values of 5% and 1% in Hypothesis Testing

Statistics / By Kanda Data / January 27, 2025

If you are conducting research, you certainly have a hypothesis for your study. Hypothesis testing is crucial in research, especially if you’re performing inferential statistical analysis. In statistical hypothesis testing, you are often faced with the choice of using an alpha value of 5% or 1% for your study.