What is the null hypothesis typically used to indicate?

The null hypothesis is a fundamental concept in statistical testing that serves as a baseline or default position. It typically asserts that there is no significant difference between groups being compared. This means that any observed differences in data can be attributed to random chance rather than a true effect or relationship. The purpose of the null hypothesis is to provide a basis for statistical testing by allowing researchers to measure whether their findings can provide enough evidence to reject this null assumption in favor of an alternative hypothesis, which posits that a significant difference or effect may exist.

In this context, the other options do not accurately capture the purpose of the null hypothesis. For instance, asserting that there is a significant difference between groups would align more with what the alternative hypothesis proposes. Similarly, stating that differences are caused by external variables reflects a possible source of influence on the observed data rather than a direct assertion about the null hypothesis itself. Lastly, suggesting that there is a correlation between variables indicates a relationship that would challenge the null hypothesis, which assumes no relationship exists by default. Thus, the hallmark of the null hypothesis is its declaration of no significant difference or relationship, making the chosen answer correct.