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Hypothesis
testing
is used to establish whether the differences exhibited by random samples can be inferred
to the populations from which the samples originated.
General
Assumptions
ü
Population
is normally distributed
ü
Random
sampling
ü
Mutually
exclusive comparison samples
ü
Data
characteristics match statistical technique
For
interval / ratio data use Ê
t-tests,
Pearson
correlation, ANOVA,
OLS regression
For
nominal / ordinal data use Ê
Difference
of proportions, chi square and related measures of association, logistic regression
State
the Hypothesis
Null
Hypothesis
(Ho): There is no difference between ___ and ___.
Alternative
Hypothesis
(Ha): There is a difference between __ and __.
Note:
The alternative hypothesis will indicate whether a 1-tailed or a 2-tailed test is utilized
to reject the null hypothesis.
Ha
for 1-tail tested: The __ of __ is greater (or
less) than the __ of __.
Set
the Rejection Criteria
This
determines how different the parameters and/or statistics must be before the null
hypothesis can be rejected. This "region of rejection" is based on alpha
( ) -- the
error associated with the confidence level. The point of rejection is known as the
critical value.
Compute
the Test Statistic
The
collected data are converted into standardized scores for comparison with the critical
value.
Decide
Results of Null Hypothesis
If
the test statistic equals or exceeds the region of rejection bracketed by the critical
value(s), the null hypothesis is rejected. In other words, the chance that the difference
exhibited between the sample statistics is due to sampling error is remote--there is an
actual difference in the population.
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