Basic Hypothesis Testing Terminology Worksheet
Choose the correct terminology for each of the below definitions from the following lists of terms: hypothesis, hypothesis
testing, rare event rule for inferential statistics, null hypothesis, alternative hypothesis, test statistic, critical region, critical
value, significance level, two-tailed test, right-tailed test, left-tailed test, traditional method, type I error, and type II error.
A procedure for testing a claim about a
property of a population.
Terminology:
Hypothesis test
The critical region is in the extreme right
region (tail) under the curve.
Terminology:
Right-tailed test
The set of all values of the test statistic that
cause us to reject the null hypothesis.
Terminology:
Critical region
A value used in making a decision about the
null hypothesis. It is found by converting
the sample statistic (such as proportion 𝑝̂ ,
the sample mean 𝑥̅ , or the sample standard
deviations) to a score (such as z, t, or χ2)
with the assumption that the null hypothesis
is true.
Terminology:
Test Statistic
If the test statistic falls within the critical
region, reject H0.
If the test statistic does not fall within the
critical region, fail to reject H0.
Terminology:
Traditional method
The critical region is in the two extreme
regions (tails) under the curve.
Terminology:
Two-tailed test
The mistake of rejecting the null hypothesis
when it is actually true.
Terminology:
Type I error
A claim or statement about a property of a
population.
Terminology:
Hypothesis
The probability that the test statistic will fall in
the critical region when the null hypothesis is
actually true. If the test statistic falls in the
critical region, we reject the null hypothesis, so
α is the probability of making a mistake of
rejecting the null hypothesis when it is true.
The mistake of failing to reject the null
hypothesis when it is actually false.
Terminology:
Type II error
The critical region is in the extreme left region
(tail) under the curve.
Terminology:
Left-tailed test
A statement that the parameter has a value that
differs somewhat from the null hypothesis.
Terminology:
Alternative hypothesis
Any value that separates the critical region
(where we reject the null hypothesis) from the
values of the test statistic that do not lead to
rejection of the null hypothesis. The critical
values depend on the nature of the null
hypothesis, the sampling distribution that
applies, and the significance level of α.
Terminology:
Terminology:
Significance level
Critical value
A statement that the value of a population
If, under a given assumption, the probability of a
parameter (such as proportion, mean, or
particular observed event is extremely small, we
standard deviation) is equal to some claimed
conclude that the assumption is probably not
value. It is assumed to be true and a conclusion correct.
is reached to either reject or fail to reject it.
Terminology:
Terminology:
Null hypothesis
Rare event rule for inferential statistics