Over the course of the last
few decades the capabilities of statistical software has improved dramatically
with obtaining output for statistical procedures of considerable complexity being
obtained with increasing ease. But to our misfortune that has not translated
into statistical analysis being any easier.
More Analysts
Within a short span of time
we may now train a student or employee to be able to output statistical data.
But that does not necessarily mean that the person is aware about the actual
meaning of the particular output or even the things that must be avoided while
interpreting the produced output along with the process of producing the output
itself.
Deal With Errors Carefully
Errors should be dealt with
carefully for and some of them must be avoided for those belonging to the class
of statistics layman but working as a SAS programmer. These errors are in all
probability will not be highlighted in capital in your SAS log which only
serves to enhance the importance of avoiding the.
Do Not Assume
For the people who have forgot
what they once knew about statistics for a variety of reasons, need to be aware
that although you indeed assume certain things, that the people producing the printouts
which serves as the base of your decision making may not necessarily follow the
steps you assume they do.
Common Problems
Common problems emerge when
an analyst starts on his work without gathering adequate information and
understanding of the data. These problems may be of various sorts like failing
to take into account several methods for sampling, overlook errors in entry of
data, poor methods of measurement and off the mark assumptions amongst other
things. SAS business analytics needs
immaculate attention to detail.
The blessing and Curse of SAS
With SAS more and more
people are able output procedures related to statistics without going in to the
finer technicalities of the concepts of statistics. However that rosy picture
is somewhat marred due to the fact that logs free from errors does not
necessarily mean interpretation or results free from errors.
The Contribution of SAS
However one must
acknowledge the contribution of SAS in making statistics accessible to a wide
variety of people and lay stress on statistics that is comprehensible by most
people rather than a minority few.
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