Question 11Null hypothesis significance testing relies on the reasoning that if the sample statistic is unlikely given a true null hypothesis, then you should1 pointincrease the sample size.reject the null hypothesis.fail to reject the null hypothesis.change the alpha level.

The correct answer is: reject the null hypothesis.

Here's the step-by-step reasoning:

1. Null hypothesis significance testing is a statistical method used to decide whether the results of an experiment are due to chance or to an actual effect.

2. The null hypothesis is the assumption that there is no effect or difference in the population. In other words, any effect or difference you see in your sample is due to chance.

3. If the sample statistic (the result you get from your sample) is unlikely given a true null hypothesis, it means that the result you got is so extreme that it would be very unlikely to get such a result just by chance.

4. Therefore, if your sample statistic is unlikely under the null hypothesis, it suggests that the null hypothesis is probably not true.

5. In this case, you should reject the null hypothesis. This doesn't necessarily prove that your alternative hypothesis is true, but it suggests that it's more likely than the null hypothesis.

6. The other options (increasing the sample size, failing to reject the null hypothesis, changing the alpha level) are not the correct responses in this situation.