A result is called “statistically significant” whenever ans. The p-value is larger than the significance level. The null hypothesis is true. The alternative hypothesis is true. The p-value is less or equal to the significance level.

A result is called "statistically significant" whenever the p-value is less or equal to the significance level. This means that the observed data is highly unlikely under the null hypothesis, leading us to reject the null hypothesis in favor of the alternative hypothesis.

Here are the steps to determine this:

1. Formulate the null hypothesis (H0) and the alternative hypothesis (H1). The null hypothesis is usually a statement of no effect or no difference while the alternative hypothesis is what you might believe to be true or hope to prove true.

2. Choose a significance level (alpha), often 0.05. This is the probability of rejecting the null hypothesis when it is true.

3. Collect and analyze the data.

4. Calculate the p-value. This is the probability of obtaining the observed data (or data more extreme) if the null hypothesis is true.

5. Compare the p-value to the significance level. If the p-value is less than or equal to the significance level, then the result is statistically significant and you reject the null hypothesis in favor of the alternative hypothesis.

So, the correct answer to your question is "The p-value is less or equal to the significance level."