What does a correlation hypothesis typically indicate?

A correlation hypothesis typically indicates that there will be a significant relationship or correlation between two variables. This type of hypothesis suggests that changes in one variable are associated with changes in another variable, although it does not imply causation. For example, a positive correlation would mean that as one variable increases, the other variable also tends to increase, and vice versa for a negative correlation. The focus is on understanding the strength and direction of the relationship between the variables rather than asserting that one variable causes changes in the other.

The other options do not accurately capture what a correlation hypothesis entails. The first option suggests that there is no relationship, which contradicts the very nature of a correlation hypothesis. The third option implies that both variables will have identical effects, which is not a requirement for correlation; the relationship may differ in strength or direction. The last option introduces external factors as determinants of correlation, which are not inherently considered in a correlation hypothesis itself.