For cross-classified data,
contingency tables
(cross-tabulations) record the frequency
for the values that fall into each possible combination of
levels from two different factors.
One of the factors is associated with the columns of the
contingency table; the other factor is associated with the
rows of the contingency table.
Individual qualitative
data values are simply grouped by the values of the classification variable.
For individual quantitative
data values, a classification may be created by defining intervals
or cutpoints to bin the data into separate groups.
To properly analyze and interpret
results of the contingency tables, you should be familiar with the
following terms and concepts:
If you are not familiar with these terms and concepts, you are advised to
consult with a statistician. Failure to understand and properly apply
contingency tables may result in drawing erroneous conclusions from your data.
Additionally, you may want to consult the following references:
Agresti, A. 1990.
Categorical Data Analysis. New York: John Wiley & Sons.
Agresti, A. 1996.
An Introduction to Categorical Data Analysis. New York: John Wiley & Sons.
Bishop, Y. M. M., Fienberg, S. E., and Holland, P. W. 1975.
Discrete Multivariate Analysis. Cambridge, MA: MIT Press.
Brownlee, K. A. 1965. Statistical Theory and Methodology
in Science and Engineering. New York: John Wiley & Sons.
Conover, W. J. 1980. Practical Nonparametric Statistics. 2nd ed.
New York: John Wiley & Sons.
Daniel, Wayne W. 1978. Applied Nonparametric Statistics.
Boston: Houghton Mifflin.
Daniel, Wayne W. 1995. Biostatistics. 6th ed.
New York: John Wiley & Sons.
Everitt, B. S. 1992. The Analysis of Contingency Tables. 2nd ed.
London: Chapman & Hall.
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