Which statement best describes the difference between a one-way ANOVA and a two-way ANOVA?

One-way ANOVA compares means across levels of a single factor; two-way ANOVA compares means across levels of two factors and can test for interaction between them.

One-way ANOVA is used only for paired data and repeated measures; two-way ANOVA is used only for independent groups and cannot test mean differences.

One-way ANOVA always requires balanced samples while two-way ANOVA only works with unbalanced samples and specifically tests whether variances differ between groups, not means.

One-way ANOVA compares two means using t-distribution adjustments; two-way ANOVA compares more than two means but cannot separate main effects from interactions when more than three factor levels exist.