## An Introduction to the Theory of StatisticsTheory of atributes - notation and terminology. Consistence of data. Association of atributes. Partial association. Manifold classification. Frequency-distributions. Averages and other measures of location. Measures of disperion. Moments and measures of skewness and kurtosis. Three impotant theoretical distributions - the binomial, the normal and the poisson. Correlation. Normal correlation. Further theory of correlation. Partial correlation. Corelation: illustrations and practical methods. Miscellaneous theorems involving the use the correlation coefficient. Simple curve fitting. Preliminary notios on sampling. The sampling of attribuctes - large samples. The sampling of variables - large samples. |

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### Contents

INTRODUCTION | 1 |

THEORY OF ATTRIBUTESNOTATION AND TERMINOLOGY | 11 |

CONSISTENCE OF DATA | 25 |

26 other sections not shown

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apply approximately arithmetic mean arrays attributes average binomial Biometrika calculated cent chapter class-frequencies class-interval classification column compared consider contingency table correlation coefficient correlation ratio corresponding death-rates denote diagram district England and Wales equal estimate Example expressed fact fluctuations of sampling frequency frequency-distribution geometric mean give given grouped height Hence inches independent individual interpolation interval Karl Pearson large samples light-eyed limits linear males mean deviation measure median method negative normal curve normal universe normally distributed number of observations number of successes obtained partial associations PEARSON percentage population positive probability proportion quantities quartile R. A. Fisher random sample range ratio regarded rows sampling distribution Sheppard's correction significance Similarly simple sampling skew square standard deviation standard error statistical stature student symmetrical theoretical theory tion total number variables variance variate zero