## BiometrySome Definitions. The development of biometry. The statistical frame of mind. Data in biology. Samples and populations. Variables in biology. Accuracy and precision of data. Derived variables. Frequency distribuitions. The handling of data. Computers. Software. Efficiency and economy in data processing. Descriptive statistics. The arithmetic mean. Other means. The median. The mode. The range. The standard deviation.Sample statistics and parametrs. Coding data before computation. Computing means and standard deviations. The coefficient of variation. Introduction to probability distribution: Binomial and poison. probability, random sampling, and hypothesis testing. the binomial distribuition. The poisson distribuition. Other discrete probability distributions. The normal probability distribuition. Estimation and hypothesis testing. introduction to the analysis of variance. Single-classification analysis of variance. Nested analysis of variance. Two-way analysis of variance. Multiway analysis of variance. Assumptions of analysis of variance. A fundamental assumption. Independence. Homogeneity of variances. Normality. Additivity. Transformations. The logarithmic, the square-root, the box-cox and the arcsine transformation. Nonparametric methods in lieu of single-classification anovas and two-way anova. Linear regression. Correlation. Multiple and curvilinear regression. Analysis of frequencies. Miscellaneous methods. Mathematical proofs. |

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### Contents

INTRODUCTION | 1 |

DATA IN BIOLOGY | 8 |

THE HANDLING OF DATA | 33 |

l DESCRIPTIVE STATISTICS | 39 |

THE NORMAL PROBABILITY DISTRIBUTION | 98 |

ESTIMATION AND HYPOTHESIS TESTING | 127 |

INTRODUCTION TO THE ANALYSIS | 179 |

SINGLECLASSIFICATION ANALYSIS | 207 |

ASSUMPTIONS OF ANALYSIS OF VARIANCE | 392 |

Ul LINEAR REGRESSION | 451 |

CORRELATION | 555 |

MULTIPLE AND CURVILINEAR REGRESSION | 609 |

ANALYSIS OF FREQUENCIES | 685 |

MISCELLANEOUS METHODS | 794 |

MATHEMATICAL PROOFS | 833 |

BIBLIOGRAPHY | 850 |

NESTED ANALYSIS OF VARIANCE | 272 |

TWOWAY ANALYSIS OF VARIANCE | 321 |

MULTIWAY ANALYSIS OF VARIANCE | 369 |

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### Common terms and phrases

alternative hypothesis analysis of variance anova table approximate binomial biological calculate chi-square classes column comparisons computed confidence limits correlation coefficient critical value curve degrees of freedom density equal equation estimate example expected frequencies experiment experimentwise error rate Expression F-distribution factor females Figure formula frequency distribution function G-test genetic given groups independent variables individual interaction linear regression logarithms magnitude mean square measure median method Model I anova multiple regression normal distribution null hypothesis observed frequencies obtain partial regression coefficients path coefficients population probability procedure proportion quantity random rank rankits rats regression line replicates represent sample mean sample sizes sample statistic Section significance test slope species standard deviation standard error Statistical Table subgroups sum of squares tion tN2t transformation treatment effects two-way anova type I error variance component wing length yield zero