In hypothesis testing, the null hypothesis typically states that there is no effect or no difference.

In hypothesis testing, the null hypothesis typically states that there is no effect or no difference.

• A. It asserts a difference exists.
• B. It asserts the alternative is false.
• C. It asserts the population parameter equals zero.
• D. It asserts no effect or no difference.

Answer: (A)

In hypothesis testing, the null hypothesis is a statement of no effect or no difference. It serves as the baseline assumption about the population parameter and is usually framed as an equality, such as the parameter equaling a specified value (often zero in many tests). The idea is to see whether the data provide enough evidence to reject this default in favor of the alternative, which says there is an effect or a difference. So the statement that there is a difference is pointing to the alternative, not the null. The notion that the alternative is false isn’t how the null is defined; failing to reject the null doesn’t prove it true, it just means there isn’t strong enough evidence against it. Finally, while the null is sometimes stated as parameter equals zero in particular tests, that’s a specific case—the null can specify other values depending on the context. The general, correct concept is that the null asserts no effect or no difference.

In hypothesis testing, the null hypothesis is a statement of no effect or no difference. It serves as the baseline assumption about the population parameter and is usually framed as an equality, such as the parameter equaling a specified value (often zero in many tests). The idea is to see whether the data provide enough evidence to reject this default in favor of the alternative, which says there is an effect or a difference. So the statement that there is a difference is pointing to the alternative, not the null. The notion that the alternative is false isn’t how the null is defined; failing to reject the null doesn’t prove it true, it just means there isn’t strong enough evidence against it. Finally, while the null is sometimes stated as parameter equals zero in particular tests, that’s a specific case—the null can specify other values depending on the context. The general, correct concept is that the null asserts no effect or no difference.