Author: Kanda Data
Natural Logarithmic Data Transformation using Excel | Simple Steps
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.
Spearman Rank Correlation Analysis | Practical Test on the Relationship Between Education Level and Performance Level
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)
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
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
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.
The Impact of Residual Variance on P-Value in Regression Analysis
When conducting linear regression analysis on your research data, you naturally hope that some independent variables significantly affect the dependent variable. Achieving this indicates that you’ve successfully selected independent variables that are presumed to influence the dependent variable.
How to Calculate Population Data Standard Deviation Using Excel
Standard deviation can be used to understand how data is distributed relative to its mean. Calculating the standard deviation in research is crucial because it determines the variability of the data.
Differences in the Formulas for Calculating Standard Deviation for Sample Data and Population Data
Standard deviation is a crucial measure in explaining how data is distributed relative to its mean. Generally, when conducting research and performing descriptive statistical analysis, the value of the standard deviation will often appear.