Biostatistics and Microbiology: A Survival Manual

Biostatistics and Microbiology enables the reader to access and apply statistical methods that generally frustrate and intimidate the uninitiated. Statistics, like chemistry, microbiology, woodworking, or sewing, requires that the individual put some time into learning the concepts and methods. This...

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Bibliographic Details
Main Author: Paulson, Daryl S. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: New York, NY : Springer New York, 2009.
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-0-387-77282-0
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505 0 # |a BioStatistics and Microbiology: Introduction -- One-Sample Tests -- Two Sample Statistical Tests, Normal Distribution -- Analysis of Variance -- Regression and Correlation Analysis -- Qualitative Data Analysis -- Nonparametric Statistical Methods -- Appendix: Tables of Mathematical Values -- Index. 
520 # # |a Biostatistics and Microbiology enables the reader to access and apply statistical methods that generally frustrate and intimidate the uninitiated. Statistics, like chemistry, microbiology, woodworking, or sewing, requires that the individual put some time into learning the concepts and methods. This book presents a step-by-step manner that eliminates the greatest obstacle to the learner, which is applying the many processes that comprise a statistical method. The author counters the fear of statistical methods by describing early in the book a step-by-step procedure to perform a statistical method - a process that we will term "the six-step procedure." All of the testing will be performed adhering to six well-defined steps, which will greatly simplify the statistical process. Each step in the sequence must be completed before moving on to the next step. In the context of microbiology, statistics can be extremely useful in making interpretations and decisions concerning collected data. Statistics, then, is a way of formally communicating the interpretation of clinical or experimental data and is particularly important when a treatment result is not clearly differentiable from another treatment. 
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