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Books > Science & Mathematics > Mathematics > Probability & statistics
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A Course in Categorical Data Analysis (Hardcover)
Loot Price: R5,482
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A Course in Categorical Data Analysis (Hardcover)
Series: Chapman & Hall/CRC Texts in Statistical Science
Expected to ship within 10 - 15 working days
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Categorical data-comprising counts of individuals, objects, or
entities in different categories-emerge frequently from many areas
of study, including medicine, sociology, geology, and education.
They provide important statistical information that can lead to
real-life conclusions and the discovery of fresh knowledge.
Therefore, the ability to manipulate, understand, and interpret
categorical data becomes of interest-if not essential-to
professionals and students in a broad range of disciplines.
Although t-tests, linear regression, and analysis of variance are
useful, valid methods for analysis of measurement data, categorical
data requires a different methodology and techniques typically not
encountered in introductory statistics courses. Developed from long
experience in teaching categorical analysis to a multidisciplinary
mix of undergraduate and graduate students, A Course in Categorical
Data Analysis presents the easiest, most straightforward ways of
extracting real-life conclusions from contingency tables. The
author uses a Fisherian approach to categorical data analysis and
incorporates numerous examples and real data sets. Although he
offers S-PLUS routines through the Internet, readers do not need
full knowledge of a statistical software package. In this unique
text, the author chooses methods and an approach that nurtures
intuitive thinking. He trains his readers to focus not on finding a
model that fits the data, but on using different models that may
lead to meaningful conclusions. The book offers some simple,
innovative techniques not highighted in other texts that help make
the book accessible to a broad, interdisciplinary audience. A
Course in Categorical Data Analysis enables readers to quickly use
its offering of tools for drawing scientific, medical, or real-life
conclusions from categorical data sets.
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