In Hypothesis
Testing the null hypothesis
will be rejected if the pvalue
is below a threshold probability level,
known as the alpha value. It is possible
that the test will give misleading results
and the wrong conclusion will be drawn.
There are two types of error:
Type
I Error 
The probability
of wrongly rejecting the null hypothesis,
that is the null hypothesis is correct,
at least to the level imposed by the
power of
the test, but the pvalue
is nevertheless smaller than the alpha
level. 
Type
II Error 
The probability
of failing to reject the null hypothesis
when it is false. That is the alternative
hypothesis is correct, but the pvalue
is nevertheless larger than the alpha
level. This is associated with the
beta risk. 
Note that in Statistical
Process Control the pvalue
is not normally explicitly defined but it
is equivalent to a sample plotting inside
or outside the control limits of a control
chart.
