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Home/Comparison Test

Category: Comparison Test

If the Data Is Not Normally Distributed, Can We Still Use the Paired Sample t-Test?

By Kanda Data / Date Jul 23.2025 / Category Comparison Test

In parametric statistical analysis, there are generally several assumptions that must be met to ensure the estimation results are unbiased. One of the key assumptions is that the data must be normally distributed. Now, if my aim is to determine the mean difference between two paired sample groups but the data is not normally distributed, can the paired sample t-test still be used? In this article, I will discuss this further.

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Alternative to One-Way ANOVA When Data Are Not Normally Distributed

By Kanda Data / Date Jun 21.2025 / Category Comparison Test

If you’re conducting research to compare the means of more than two sample groups, one-way ANOVA is a commonly used statistical test. However, using this test comes with certain assumptions that must be met, specifically, that the data are normally distributed and homogenous.

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Comparison Test

The Difference Between Pearson Correlation and Spearman Rank Correlation in Research

By Kanda Data / Date Aug 16.2024

For those currently conducting data analysis, correlation tests are commonly used to measure the relationship between two variables. However, not all correlation tests are suitable for every type of data. As we all know, data types and characteristics can vary.

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Comparison Test

Difference between Paired t-test and Independent t-test

By Kanda Data / Date May 02.2024

A deep understanding of the difference between paired t-test and independent t-test is crucial for researchers. A strong grasp of both methods is key to making informed decisions based on analyzed data. Paired t-test and independent t-test are used to determine the difference in means between two sample groups.

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Comparison Test

Understanding the Difference Between Paired T-Test and Wilcoxon Test in Statistics

By Kanda Data / Date Mar 15.2024

In the realm of statistics, associative tests play a crucial role in examining differences, relationships, and influences between variables. One common form of associative test is the test for differences, which aims to compare the means of two or more sample groups.

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Comparison Test

Understanding the t-test for non-normally distributed data

By Kanda Data / Date Sep 18.2023

For researchers aiming to explore the differences between two sample groups, the t-test is a viable option. According to theory, the t-test can determine differences between two sample groups, whether they are paired or independent.

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Comparison Test

How to Distinguish Between Paired Sample T-Test and Independent Sample T-Test

By Kanda Data / Date Aug 28.2023

The t-test is one of the associative tests researchers frequently use to examine the difference in mean values between variables. This test is applicable only when dealing with two groups of samples. If the tested variables differ among more than two sample groups, then the t-test cannot be utilized.

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Comparison Test

Differences in the use of paired sample t-test and independent sample t-test

By Kanda Data / Date Jul 18.2023

The t-test is commonly used to test the mean difference between two samples. The t-test can be performed on paired samples as well as independent samples. When should we use the paired sample t-test and when should we use the independent sample t-test?

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  • Assumptions of Linear Regression
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