T-test vs Z-test: Key Differences and When to Use Each #3716905 (License: Personal Use)

The image displays two rounded rectangular cards-one yellow labeled "T-test", the other blue labeled "Z-test"-representing two widely used inferential statistical methods. The T-test is typically applied when population variance is unknown and sample sizes are small (n < 30), while the Z-test assumes known population variance and larger samples. Both are used for comparing means, but their underlying assumptions dictate appropriate usage in research and data analysis.

This image is commonly used on educational or statistical methodology web pages to introduce or contrast parametric hypothesis testing techniques. It supports user intent to quickly grasp core differences between T and Z tests, often appearing in tutorials, blog posts, or course materials for students and analysts.