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Home/inferential statistics

Tag: inferential statistics

Statistics

Why Should Data Transformation Be Done Only Once?

By Kanda Data / Date Jul 11.2024

Data transformation is an essential step in inferential statistical analysis. It can be a solution to ensure that research data meets certain required statistical model assumptions, such as normality, linearity, and homoscedasticity.

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Statistics

Data Transformation to Address Non-Normally Distributed Data

By Kanda Data / Date Jun 18.2024

The assumption that data must be normally distributed is often a prerequisite for using certain inferential statistical tests. However, sometimes the test results do not meet expectations, indicating that the data is not normally distributed.

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Statistics

Understanding the Essence of the Difference Between Descriptive Statistics and Inferential Statistics in Research

By Kanda Data / Date Mar 20.2024

In conducting research, understanding the basic theory of statistics becomes crucial for researchers. Why is this so important? Because to extract accurate conclusions from research data, careful analysis using statistical tools is needed.

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Data Analysis in R

How to Test for Normality in Linear Regression Analysis Using R Studio

By Kanda Data / Date Nov 21.2023

Testing for normality in linear regression analysis is a crucial part of inferential method assumptions, requiring regression residuals to be normally distributed. Residuals are the differences between observed values and those predicted by the linear regression model.

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Statistics

Difference between Descriptive Statistics and Inferential Statistics for Research Activities

By Kanda Data / Date Jun 19.2022

In research activities, researchers need to understand the use of descriptive statistics and inferential statistics. Researchers can use one of them or combine both descriptive and inferential statistics.

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