The Oxford Dictionary of Statistical TermsThe Oxford Dictionary of Statistical Terms is the much-awaited sixth edition of the acclaimed standard reference work in statistics, published on behalf of the International Statistical Institute. The first edition, known as the Dictionary of Statistical Terms, was edited in 1957 by the late Sir Maurice Kendall and the late Dr. W.R. Buckland. As one of the first dictionaries of statistics it set high standards for the subject and became a well-respected reference. This new edition has been carefully updated and extended to include the most recent terminology and techniques in statistics. Significant revision and expansion from an international editorial board of senior statisticians has resulted in a comprehensive reference text, which includes 30%, more material than previous editions. Ideal for all who use statistics in the workplace and in research including all scientists and social scientists, especially in law, politics, economics, finance, business and history, it is an indispensable reference. |
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Contents
Section 1 | 1 |
Section 2 | 24 |
Section 3 | 55 |
Section 4 | 104 |
Section 5 | 126 |
Section 6 | 144 |
Section 7 | 159 |
Section 8 | 177 |
Section 15 | 291 |
Section 16 | 299 |
Section 17 | 326 |
Section 18 | 333 |
Section 19 | 357 |
Section 20 | 402 |
Section 21 | 418 |
Section 22 | 423 |
Section 9 | 192 |
Section 10 | 212 |
Section 11 | 215 |
Section 12 | 224 |
Section 13 | 247 |
Section 14 | 280 |
Section 23 | 427 |
Section 24 | 435 |
Section 25 | 437 |
439 | |
Common terms and phrases
alternative analysis applied approximation associated asymptotic average bivariate block called characteristic coefficient components conditional confidence constant continuous correlation corresponding curve decision defined denote density dependent derived determined developed deviation distribution function effect equal equation error estimator example expected experiment experimental expression factor frequency given hypothesis independent individual inequality interval introduced known least likelihood limit linear mathematical matrix mean measure method multivariate normal normal distribution observations obtained occurs original parameter particular period Poisson population possible probability problem procedure proportion proposed provides quantity random variables range rank ratio referred regarded region regression relative represented response sample selection sense sometimes space specified square standard statistic stochastic process successive term theorem theory tion transformation treatments unit usually values variance variation weights zero