http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
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.
Comparison of means of two or more groups.
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. --Book Jacket.
Are the data normally distributed? -- Describing the normal distribution -- Testing the difference between two groups -- Wat if the data are not normally distributed? -- Chi-square contingency tables -- One-way analysis of variance (anova) -- Post hoc tests -- Is one set of data more variable than another? -- Statistical power and sample size -- One-way analysis of variance (random effects model) : the nested or hierarchical design -- Two-way analysis of variance -- Two-factor analysis of variance -- Split-plot analysis of variance -- Repeated-measures analysis of variance -- Correlation of two variables -- Limits of agreement -- Nonparametric correlation coefficients -- Fitting a regression line to data -- Using a regression line for prediction and calibration -- Comparison of regression lines -- Nonlinear regression : fitting an exponential curve -- Nonlinear regression : fitting a general polynomial-type curve -- Nonlinear regression : fitting a logistic growth curve -- Nonparametric analysis of variance -- Multiple linear regression -- Stepwise multiple regression -- Classification and dendrograms -- Factor analysis and principal components analysis -- Which test to use : table -- Which test to use : key -- Glossary of statistical terms and their abbreviations -- Summary of sample size procedures for different statistical tests.
Richard A. Armstrong and Anthony C. Hilton.
Includes bibliographical references and index.
Hoboken, NJ : Wiley-Blackwell Pub, ©2011