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  2. A t test is a statistical hypothesis test that assesses sample means to draw conclusions about population means. Frequently, analysts use a t test to determine whether the population means for two groups are different.

  3. T-tests enable you to make data-driven decisions by quantifying the likelihood that there’s a significant difference between two groups rather than relying only on observational evidence, like metrics.

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  4. The t test tells you how significant the differences between group means are. It lets you know if those differences in means could have happened by chance. The t test is usually used when data sets follow a normal distribution but you don’t know the population variance.

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  5. Oct 4, 2024 · A t-test is an inferential statistic used in hypothesis testing to determine if there is a statistically significant difference between the means of two samples.

  6. Apr 11, 2020 · What is a t-test? Imagine you are running an experiment where you want to compare two groups and quantify the difference between them. For example: Compare if the people of one country are taller than people of another one. Compare if the brain of a person is more activated while watching happy movies than sad movies.

  7. Apr 20, 2016 · Understanding t-Tests: t-values and t-distributions. T-tests are handy hypothesis tests in statistics when you want to compare means. You can compare a sample mean to a hypothesized or target value using a one-sample t-test. You can compare the means of two groups with a two-sample t-test.

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