## Biostatistics: A Foundation for Analysis in the Health SciencesLike its predecessors, this edition stresses intuitive understanding of principles rather than learning by mathematical proof. Provides broad coverage of statistical procedures used in all the health science disciplines. This version contains a greater emphasis on computer applications (MINITAB command instruction is demonstrated) for most of the statistical techniques. New to this edition: computer printouts demonstrating the SASŪ software package, determination of sample size to control Type I and Type II errors, the Fisher Exact Test, the Repeated Measures Design, the Mantel-Haenszel Statistic. More than 250 of the examples and exercises are based on actual data obtained directly from researchers in the health field and from reports of research findings published in health sciences literature. |

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### Contents

Introduction to Biostatistics | 1 |

Descriptive Statistics | 15 |

Some Basic Probability Concepts | 60 |

Copyright | |

14 other sections not shown

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### Common terms and phrases

95 percent confidence American Journal analysis of variance approximately normally distributed assume assumptions central limit theorem chapter chi-square class intervals Clinical completely randomized design conclude Construct a 95 critical value data provide sufficient Decision Rule degrees of freedom determine difference disease drug effect equal estimate example expected frequencies Figure H0 is true Health hypothesis testing independent variables level of significance male measurements median MINITAB multiple nonrejection regions normally distributed population null hypothesis observations obtain parameter patients percent confidence interval population mean population proportion population variances procedure provide sufficient evidence random variable ratio regression analysis regression equation reject H0 reject the null rejection region relationship risk factor sample means sampled population sampling distribution scores simple random sample smoking Solution standard deviation standard error standard normal distribution Statistical Decision subjects sum of squares test statistic test the null treatment weight