T-test
A statistical test used to compare the means of two groups to determine if they are significantly different from each other.
What is T-test?
A t-test evaluates whether the difference between two sample means is large enough to conclude that their corresponding population means differ, taking into account the variance and sample size. It assumes the data is roughly normally distributed and is typically used when the sample size is relatively small or the population standard deviation is unknown.
Why T-test Matters
It allows researchers to infer whether observed differences between two groups in a sample represent true differences in the population or are merely due to random sampling variation.
Example
A psychologist uses a t-test to compare the mean stress levels of employees who have flexible working hours versus those who have fixed working hours.
Common Mistakes
- Using a t-test to compare more than two groups (which requires ANOVA instead).
- Ignoring the assumption of normally distributed data, especially in small samples.