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We are given a hypothesis.

A hypothesis test is to be performed to decide whether the mean wing lengths for the two subspecies (migratory and nonmigratory) are different.

A variable is an attribute or a characteristic that can be measured. The value of the variable may differ for each and every unit. That is, a variable is defined as the characteristic which is recorded for each case.

The wing lengths of two subspecies are recorded in the article.

So the variable in this study is wing lengths

The population includes all the individuals of interest that are being examined. In other words, the collection of all people, items, or objects that are required for a specific study is defined as the population.

Wing lengths of two subspecies are recorded. They are migratory subspecies and nonmigratory subspecies.

So the two populations are migratory subspecies and nonmigratory subspecies.

Let us assume that ${\mathrm{μ}}_1$denotes the mean wing length of migratory subspecies and ${\mathrm{μ}}_2$denotes the mean wing length of nonmigratory subspecies.

The null hypothesis is defined as

$H_0:$There is no significant difference between the mean wing length of migratory subspecies and nonmigratory subspecies.

$H_0:{\mathrm{μ}}_1={\mathrm{μ}}_2$

The alternative hypothesis is defined as

role="math" localid="1652781176688" $H_a:$There is a significant difference between the mean wing length of migratory subspecies and nonmigratory subspecies.

$H_a:{\mathrm{μ}}_1≠{\mathrm{μ}}_2$

As our alternative hypothesis suggest that the mean of the first population is not equal to the mean of the second population.

So the hypothesis can be classified as a two-tailed test.