Good statistical design of experimental and analytical methods is a fundamental component of successful research. The set of tools that has evolved to implement these processes of design and analysis is called Biostatistics. Using these tools blindly or by rote is a recipe for failure. The Biostatistics Cookbook is intended for research scientists who want to understand why they do a particular test or analysis as well as how to do it. It is meant as an interpreter as well as a guide, helping the researcher to illuminate and communicate his or her results as accurately, concisely, and universally as possible.
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Introduction. 1: Description. Populations, Distributions, and Samples. Measures of Central Tendency. Data Dispersion, Noise, and Error. Graphics. 2: Inference. Comparing a Sample Mean to a Population with Known Mean and Variance - The One Sample z-Test. Comparing a Sample Mean to a Population with Known Mean and Unknown Variance - The One Sample t-Test. Comparing Before and After Data - The Two Sample Paired t-Test. Comparing Two Means - The Two Sample Unpaired t-Test. Comparing Three or More Means - The One Way Analysis of Variance. Comparing Two or More Proportions: Proportions Tests and Chi-Square (chi2). Distribution-Free Measures: Non-Parametric Tests. 3: Estimation. Data Relationships: Association and Correlation. Data Relationships: Mathematical Models and Linear Regression. Complex Data Relationships: Mathematical Models and Non-Linear Regression. 4: Design of a Statistical Experiment. Index.
Biostatistics Cookbook by Michelson Seth, 9780792338840, Springer, 1996, Hardcover
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