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Terms and Definitions

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Null Hypothesis (H_{0})

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The Statement containing a *null*, or zero, difference. It
is the null hypothesis which undergoes the testing procedure, whether it
is the original claim or not.

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Alternative Hypothesis (H_{A})

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The statement that must be true if the null hypothesis is false.

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Test Statistic

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A sample statistic or value based upon a sample population. This
is the data used in deciding the validity of a given hypothesis.

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Type I Error

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The mistake of rejecting the null hypothesis when it is true.

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Type II Error

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The mistake of failing to reject the null hypothesis when it is false.

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Rejection Region

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The set of all values of the test stastic that would cause us to reject
the null hypothesis. This Area is defined by the Critical Value(s).

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Critical Value(s)

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The value(s) that separates the rejection region from the values of
the test statistic that would not lead to rejection of the null hypothesis.
The Critical Value(s) are dependent on the hypotheses, the relevant sample
distribution, and the level of significance.

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Significance Level

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The probability of rejecting the null hypothesis when it is true.
Typical values of this are 0.05 and 0.01.

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Two-Tailed Hypothesis Test

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A Hypothesis Test where the rejection region is divided equally between
2 critical values at the extremities of the distribution. A two-tailed
test is applied when an alternative hypothesis (H_{A}) equals a given
quantity (H_{A} = *x* ).

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Right-Tailed Hypothesis Test

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A Hypothesis Test where the rejection region is located to the extreme
right of the distribution. A right-tailed test is conducted when the
alternative hypothesis (H_{A}) contains the condition H_{A}
> *x* (greater than a given quantity).

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Left-Tailed Hypothesis Test

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A Hypothesis Test where the rejection region is located to the extreme
left of the distribution. A left-tailed test is conducted when the
alternative hypothesis (H_{A}) contains the condition H_{A}
< *x* (less than a given quantity).

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