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Introductory Statistics for the Health Sciences takes students on a
journey to a wilderness where science explores the unknown,
providing students with a strong, practical foundation in
statistics. Using a color format throughout, the book contains
engaging figures that illustrate real data sets from published
research. Examples come from many areas of the health sciences,
including medicine, nursing, pharmacy, dentistry, and physical
therapy, but are understandable to students in any field. The book
can be used in a first-semester course in a health sciences program
or in a service course for undergraduate students who plan to enter
a health sciences program. The book begins by explaining the
research context for statistics in the health sciences, which
provides students with a framework for understanding why they need
statistics as well as a foundation for the remainder of the text.
It emphasizes kinds of variables and their relationships
throughout, giving a substantive context for descriptive
statistics, graphs, probability, inferential statistics, and
interval estimation. The final chapter organizes the statistical
procedures in a decision tree and leads students through a process
of assessing research scenarios. Web ResourceThe authors have
partnered with William Howard Beasley, who created the
illustrations in the book, to offer all of the data sets, graphs,
and graphing code in an online data repository via GitHub. A
dedicated website gives information about the data sets and the
authors' electronic flashcards for iOS and Android devices. These
flashcards help students learn new terms and concepts.
Introductory Statistics for the Health Sciences takes students on a
journey to a wilderness where science explores the unknown,
providing students with a strong, practical foundation in
statistics. Using a color format throughout, the book contains
engaging figures that illustrate real data sets from published
research. Examples come from many areas of the health sciences,
including medicine, nursing, pharmacy, dentistry, and physical
therapy, but are understandable to students in any field. The book
can be used in a first-semester course in a health sciences program
or in a service course for undergraduate students who plan to enter
a health sciences program. The book begins by explaining the
research context for statistics in the health sciences, which
provides students with a framework for understanding why they need
statistics as well as a foundation for the remainder of the text.
It emphasizes kinds of variables and their relationships
throughout, giving a substantive context for descriptive
statistics, graphs, probability, inferential statistics, and
interval estimation. The final chapter organizes the statistical
procedures in a decision tree and leads students through a process
of assessing research scenarios. Web ResourceThe authors have
partnered with William Howard Beasley, who created the
illustrations in the book, to offer all of the data sets, graphs,
and graphing code in an online data repository via GitHub. A
dedicated website gives information about the data sets and the
authors' electronic flashcards for iOS and Android devices. These
flashcards help students learn new terms and concepts.
If you conduct research with more than two groups and want to find
out if they are significantly different when compared two at a
time, then you need Multiple Comparison Procedures. Using examples
to illustrate major concepts, this concise volume is your guide to
multiple comparisons. Toothaker thoroughly explains such essential
issues as planned vs. post-hoc comparisons, stepwise vs.
simultaneous test procedures, types of error rate, unequal sample
sizes and variances, and interaction tests vs. cell mean tests.
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