This book is aimed primarily at microbiologists who are undertaking research, and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it even more essential that microbiologists understand the basic principles of statistics.
Statistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. In addition, most statistical software commercially available is complex and difficult to use. Hence, it is easy to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment.
The purpose of this book is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The book is presented as a series of 2018Statnotes', many of which were originally published in the 2018Microbiologist' by the Society for Applied Microbiology, each of which deals with various topics including the nature of variables, comparing the means of two or more groups, non-parametric statistics, analysis of variance, correlating variables, and more complex methods such as multiple linear regression and factor analysis. In each case, the relevant statistical methods are illustrated with scenarios and real experimental data drawn from experiments in microbiology. The text will incorporate a glossary of the most commonly used statistical terms and a section to aid the investigator to select the most appropriate test.
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Dr. Richard Armstrong is a?Lecturer for the School of Life and Health Sciences for Aston University. His research interests include?Neuropathology of Alzheimer's Disease; Lichen Biology and Ecology. He has?published in many?peer reviewed journals.
Dr. Anthony C. Hilton is a Senior Lecturer in Microbiology and the UG Programme Director at Aston University in the School of Life and Health Sciences. His research interests include applied microbiology (food and clinical), molecular microbiology, salmonella, campylobacter, MRSA and Escherichia?coli 0157, clostridium difficult, and molecular typing of microorganisms.?In addition to contributing to various peer reviewed journals, he is also member of the Molecular Biosciences Research Group.
Statistical Analysis in Microbiology: StatNotes has been designed specifically for microbiologists who are involved in experimental research and need to draw accurate conclusions from their findings. It features twenty-eight StatNotes that together enable you to understand the basic principles of statistics, choose the correct statistical methods to analyze your experimental data, and work with a variety of commercially available statistical software packages. These StatNotes are based on a series of popular articles published in Microbiologist, the official magazine of the Society for Applied Microbiology. They explore a variety of topics in statistics that are essential for analyzing experimental data, including:
Nature of variables
Comparison of means of two or more groups
Non-parametric statistics
Analysis of variance
Correlation of variables
Multiple linear regression and factor analysis
Throughout the book, the logic and mechanics of each statistical test presented are carefully explained. Moreover, each statistical test is illustrated with examples drawn from actual experiments and research data in microbiology. As a result, you can clearly see how each test is interpreted and what types of conclusions can be drawn from the research data.
In the back of the book, you'll find a glossary of statistical terms and their abbreviations as well as a summary of sample size calculations. You'll also find two appendices that help you select the most appropriate statistical tests based on the type of research you're conducting and the type of data that you're gathering.
Given the wide variety of statistical software packages, it's essential that you understand the underlying principles and purpose of each statistical method; applying an inappropriate statistical test can easily lead to the wrong conclusions. Written specifically for microbiologists, the highly acclaimed and popular StatNotes enable you to choose which statistical methods should be applied to analyze and draw correct conclusions from your experimental data.
Statistical Analysis in Microbiology: StatNotes has been designed specifically for microbiologists who are involved in experimental research and need to draw accurate conclusions from their findings. It features twenty-eight StatNotes that together enable you to understand the basic principles of statistics, choose the correct statistical methods to analyze your experimental data, and work with a variety of commercially available statistical software packages. These StatNotes are based on a series of popular articles published in Microbiologist, the official magazine of the Society for Applied Microbiology. They explore a variety of topics in statistics that are essential for analyzing experimental data, including:
Nature of variables
Comparison of means of two or more groups
Non-parametric statistics
Analysis of variance
Correlation of variables
Multiple linear regression and factor analysis
Throughout the book, the logic and mechanics of each statistical test presented are carefully explained. Moreover, each statistical test is illustrated with examples drawn from actual experiments and research data in microbiology. As a result, you can clearly see how each test is interpreted and what types of conclusions can be drawn from the research data.
In the back of the book, you'll find a glossary of statistical terms and their abbreviations as well as a summary of sample size calculations. You'll also find two appendices that help you select the most appropriate statistical tests based on the type of research you're conducting and the type of data that you're gathering.
Given the wide variety of statistical software packages, it's essential that you understand the underlying principles and purpose of each statistical method; applying an inappropriate statistical test can easily lead to the wrong conclusions. Written specifically for microbiologists, the highly acclaimed and popular StatNotes enable you to choose which statistical methods should be applied to analyze and draw correct conclusions from your experimental data.
"About this title" may belong to another edition of this title.
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