Because our p-value is LESS than the alpha…
… we reject the null. There IS sufficient evidence to conclude that (state null hypothesis in context/answer the question).
When conducting a hypothesis test, the p-value is compared to the level of significance (alpha) to determine if the null hypothesis should be rejected or not. If the p-value is less than the alpha, it means that the test results are statistically significant and we reject the null hypothesis.
In other words, if the p-value is less than the alpha, then the probability of getting the observed test statistic assuming the null hypothesis is true is very low. This implies that the observed results are unlikely to occur by chance, and it is therefore reasonable to conclude that the null hypothesis is not true and that the alternative hypothesis is likely to be true.
For example, if we set the level of significance to 0.05 (alpha = 0.05) and get a p-value of 0.01, we would reject the null hypothesis and accept the alternative hypothesis. This means that we have enough evidence to conclude that the observed results are not due to chance, and that a real effect exists in the population.
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