Perform T-Tests in R I Types and Assumptions

Perform T-Tests in R I Types and Assumptions
As a data analyst with a Ph.D. in data science and five years of freelance experience, I often think about the intricacies of statistical tests. One such test that has always intrigued me is the T-test. Have you ever wondered how researchers determine whether there is any statistically significant difference between two groups? Or how they make confident decisions based on data?  The answer lies in the T-Test, a statistical hypothesis test that allows us to compare means and assess whether the studied groups are distinct. Table of Contents Key Points The t-test is a widely used statistical method for assessing whether there is a significant difference in means between two groups or samples. It is a parametric test that considers the variability within each group when comparing means. Three main types of t-tests are Independent (also known as two-sample), Paired (also known as Dependent), and One-Sample T-test; the two-sample t-test is often utilized when you want to test unequal or var.equal …

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