Shaffer, J. P. "Multiple Hypothesis Testing." 46,561-584, 1995.

Let's take a closer look at how a hypothesis is used, formed, and tested in scientific research.

When we are talking about hypotheses:

Explain your answer.


A researcher hypothesizes that electrical stimulation of the lateral habenula will result in a decrease in food intake (in this case, chocolate chips) in rats.

We are testing the hypothesis that the population means are equalfor the two samples.

Performs one and two sample t-tests on vectors of data.

If the biologist set her significance level α at 0.05 and used the critical value approach to conduct her hypothesis test, she would reject the null hypothesis if her test statistic t* were less than -1.6939 (determined using statistical software or a t-table):

Here are some examples of hypothesis statements:

A hypothesis is usually written in the form of an if/then statement, according to the . This statement gives a possibility (if) and explains what may happen because of the possibility (then). The statement could also include "may."

This is the critical value that we need if we want to reject the null hypothesis.


a character string describing the alternativehypothesis.

It depends on how you are conducting the t-tests. For instance, in . If your hypothesis (before examining any data) is "there is no DIF for this CLASS in comparison to that CLASS on this item", then the reported probabilities are correct.

If (p/8) ≤.05 then reject hypothesis 2.

The absolute value of the test statistic for our example, 12.62059, is greater than the critical value of 1.9673, so we reject the null hypothesis and conclude that the two population meansare different at the 0.05 significance level.

Our t-Statistic for the hypothesis that B1 = 1 is simply:

In the scientific method, whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment.

Our t-Statistic for the hypothesis that B2 = -0.4 is simply:

In the previous example, we set up a hypothesis to test whether a sample mean was close to a population mean or desired value for some soil samples containing arsenic. On this page, we establish the statistical test to determine whether the difference between the sample mean and the population mean is significant. It is called the t-test, and it is used when comparing sample means, when only the sample standard deviation is known.

The quality control specialist's hypotheses are:

Notice that all of the statements, above, are testable. The primary trait of a hypothesis is that something can be tested and that those tests can be replicated, according to Midwestern State University.

Hypothesis Testing will be available on

If you have 20 items, then one is expected to fail the p ≤ .05 criterion. So if your hypothesis (before examining any data) is "there is no DIF in this set of items for any CLASS", then adjust individual t-test probabilities accordingly.