Which of the following is a valid one-sample hypothesis test?

• A. Chi-square test for independence
• B. Two-sample $t$-test for comparing means
• C. One-sample $t$-test for the mean
• D. $ANOVA$ for comparing multiple group means

Answer: (C)

Verified step by step guidance

1. Understand what a one-sample hypothesis test is: it involves testing a hypothesis about a population parameter (like the mean) using data from a single sample.
2. Review each option to see if it fits the one-sample context:
3. Chi-square test for independence is used to test the relationship between two categorical variables in a contingency table, typically involving two or more samples or groups, so it is not a one-sample test.
4. Two-sample t-test compares the means of two independent groups, so it involves two samples, not one.
5. ANOVA (Analysis of Variance) compares means across three or more groups, which also involves multiple samples, not one.
6. One-sample t-test for the mean tests whether the mean of a single sample differs from a known or hypothesized population mean, making it a valid one-sample hypothesis test.