Moreover, some users of statistics argue that we should always work with the two-sided alternative. It turns out it's much easier to disprove a hypothesis than to positively prove one.

If the hypothesis is tested and found to be false, using statistics, then a connection between hyperactivity and sugar ingestion may be indicated.

There are clear exceptions to those alternate hypotheses, so if you test the wrong plants, you could reach the wrong conclusion. Keep in mind the underlying fact that hypothesis testing is based on probability laws; therefore, we can talk only in terms of non-absolute certainties.

The short answer is that it is part of the scientific method. If our p-value is greater than alpha, then we fail to reject the null hypothesis.

So I would definitely pick choice C. The null hypothesis is a general statement that can be used to develop an alternate hypothesis, which may or may not be correct. Books have been filled with the collected criticism of significance testing. The machine is designed to dispense milliliters of liquid on the medium size setting.

In a mathematical formulation of the alternative hypothesis, there will typically be an inequality, or not equal to symbol. Hence, under this two-tailed null hypothesis, the observation receives a probability value of 0.

Explicitly reporting a numeric result eliminates a philosophical advantage of a one-tailed test. And so and we care about the population of students at the school.

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Writing null and alternative hypotheses (practice)