What type of effects does the alternative hypothesis suggest?

The alternative hypothesis is a fundamental concept in statistical hypothesis testing. It posits that there is a significant difference or relationship between the variables being studied. When researchers formulate an alternative hypothesis, they are typically looking to demonstrate that a change has taken place or that a particular phenomenon exists, as opposed to merely attributing observations to random variation.

In this context, the alternative hypothesis challenges the null hypothesis, which often suggests that there are no effects, no differences, or that any observed changes can be attributed to chance. By positing a significant difference or relationship, the alternative hypothesis opens the door for researchers to explore meaningful patterns and effects in their data, contributing to the understanding of the subject under study.

The options that suggest negligible effects, no effect at all, or random chance outcomes do not align with the nature of the alternative hypothesis, which seeks to identify and assert the presence of significant relationships or differences. Through statistical testing, evidence is gathered to potentially support the alternative hypothesis over the null certainty, reinforcing its role in research for decision making.