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Statistics for the Clinician II: The T-test, Its Versions, and Its Alternatives
Sherwin Thiyagarajan1, Paul Abboud2, Reza Ehsanian2
1Department of Computer Science, University of New Mexico, Albuquerque, NM, USA.
Seminars in Cardiothoracic and Vascular Anesthesia
|April 20, 2026
Summary
This article introduces the t-test, a statistical method for comparing sample averages to draw conclusions about population averages. It explains the t-test
Area of Science:
- Biostatistics
- Clinical Research Methodology
Background:
- The t-test is a fundamental statistical tool used in research.
- It enables the comparison of sample means to infer population means.
Purpose of the Study:
- To provide clinicians with a basic understanding of the t-test.
- To explain the reasoning, applications, and implications of the t-test in clinical research.
Main Methods:
- The article describes three basic forms of the t-test.
- It covers applications, alternatives, and related concepts.
- Technical jargon is minimized for accessibility.
Main Results:
- The t-test allows evidence-based conclusions about population averages from sample data.
- Understanding the t-test is crucial for interpreting clinical research findings.
Conclusions:
- The t-test is an accessible and valuable statistical technique for clinicians.
- This introduction aims to demystify the t-test for those with limited statistical backgrounds.
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