One-sample t-test
Is this group's mean different from a known value?
When should I use One-sample t-test?
You are comparing one set of measurements against a known value, so a one-sample t-test is appropriate provided the values are roughly normally distributed.
What your data needs to look like
One group of measurements, and the value you are comparing it against.
What One-sample t-test assumes
Chavery checks each of these against your data before it runs the test, and says whether it held. It does not ask you to assert them.
- Normality (Shapiro-Wilk)
- The values are spread roughly symmetrically around their average, rather than bunched at one end or dominated by a few extreme readings. When this one fails, Chavery runs Wilcoxon signed-rank instead.
What Chavery offers instead, and when
- Wilcoxon signed-rank — when normality does not hold.
What Chavery does with it
It checks the assumptions first and says whether each one held. When an assumption fails it names the alternative test rather than running this one anyway.
Then it reports the statistic, the p-value, a confidence interval and an effect size, and writes the sentence you would put in your results chapter. The same numbers always give the same answer; nothing is generated by a language model.
Reporting it
A p-value on its own is not a result. Chavery reports the effect size beside it, because a difference can be statistically significant and too small to matter, and an examiner will ask which yours is. More on effect size.
Not sure this is the test you need? Work through the question Chavery asks and it will name the test your design calls for.
Related tests
- Independent t-test — Do two separate groups differ on average?
- Kruskal-Wallis — Three or more groups, without assuming normality.
- Mann-Whitney U — Two groups, without assuming normality.
- One-way ANOVA — Three or more groups.
- Paired t-test — Before and after, in the same people.
- Welch's t-test — Two groups with unequal spread.
- Wilcoxon signed-rank — Before and after, without assuming normality.
Run it on your own data. Paste your numbers and Chavery runs One-sample t-test with the assumption checks and the reported sentence — no project needed. Open the analysis tool, or let Chavery choose the test for you.