Why Use a t-Statistic?

Q: Why Use a t-Statistic?

This question evaluates understanding of the t-statistic as a standardized measure for testing whether an estimated effect differs from zero, covering how effect size, variance, and sample size influence the statistic, its relationship to confidence intervals and p-values, and the assumptions and limitations that can make it misleading.

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In the context of an A/B test or a linear regression, explain why the t-statistic is a useful measure for evaluating whether an estimated effect differs from zero.

Your answer should address:

The definition of the t-statistic.
Why it is more informative than looking at the raw coefficient alone.
How effect size, variance, and sample size affect it.
Its relationship to confidence intervals and p-values.
The assumptions required for interpreting it correctly, and situations where the t-statistic can be misleading.

Why Use a t-Statistic?

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