Tag: t-test
Alternative to the t-test When Data Are Not Normally Distributed
The t-test is one of the most popular methods for comparing the means of two sample groups. In practice, the t-test can be used for two paired sample groups or two independent sample groups. We can perform this difference test using a paired-samples t-test or an independent-samples t-test, depending on the characteristics of the data being analyzed.
If the Data Is Not Normally Distributed, Can We Still Use the Paired Sample t-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.
Differences in the use of paired sample t-test and independent sample t-test
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?
Paired Sample T-test: Definition, Analysis Stage, and Interpreting the Results
Researchers often use the t-test to analyze differences in two sample groups. The t-test that researchers often use consists of the paired sample t-test and the independent sample t-test.
Comparison of Two Sample Dependent (Paired t-test)
The comparison of two paired samples becomes interesting to discuss this time. This two-sample comparison test is often analyzed using a paired t-test. Many researchers or students who are conducting research choose to use this test.
Difference Among Regression, Correlation, and Comparative Test
The ability to understand statistical analysis is increasingly important for us. Researchers, practitioners, and students often use statistical analysis to process research results. In economics, agribusiness, and social sciences, we often observe the relationship of variables associated with each other.