Null Hypothesis is defined as what?

• A. A prediction that there is no real, true difference between means being compared
• B. A statement that there is a real difference between means
• C. A claim about population variance
• D. A decision rule for accepting data

Answer: (A)

In hypothesis testing, the null hypothesis is a statement of no effect or no difference. When comparing means, it asserts that the population means are equal, so any observed difference in the sample is due to random sampling variability rather than a real difference in the populations. This default position—no real difference—lets us measure how surprising the data are under that assumption.

The option that describes this as a prediction that there is no real, true difference between the means being compared matches the null hypothesis precisely. The alternative hypothesis would claim there is a real difference, which is not what the null states. The idea of a claim about population variance or a general decision rule for accepting data does not define the null in the context of comparing means. In practice, we test the null and use the results to decide whether there is enough evidence to conclude a real difference exists.