Final answer:
Independent-groups designs involve different participants in separate groups for each condition, whereas within-groups designs use the same participants for all conditions. Independent-groups can be analyzed with an independent samples t test or one-way ANOVA, while within-groups involve comparing participant performance across different conditions.
Step-by-step explanation:
The main difference between independent-groups designs and within-groups designs in experimental research lies in how participants are assigned to groups and exposed to variables. In independent-groups designs, also known as between-subjects designs, different participants are placed into separate groups where each group represents a different condition or level of the independent variable. For instance, an experimental group receives the manipulation being tested, while a control group does not. This can be analyzed using statistical tests like the independent samples t test for two groups or one-way ANOVA for more than two groups.
By contrast, in within-groups designs, also known as within-subjects or repeated measures designs, the same participants are used in all conditions. This means that each participant experiences all levels of the independent variable at different times. For example, in a study investigating the effectiveness of a new math textbook, students would act as their own control by being tested before and after using the textbook.