An entertaining, but extremely useful introduction to statistics. The author approaches the subject in his own inimitable style which combines clarity with humour. This book is a much revised and enlarged version of the author's successful first edition published in 1976.
Introductory Medical Statistics aims to equip the reader with a useful working knowledge of statistics. Essential background material is covered first and the criteria for statistical significance are then discussed, followed by the various statistical tests leading on to the analysis of variance, the Wilcoxon rank sum test, the sign text, survival rate calculations, and regression and correlation. Real examples ranging from the aftermath of Chernobyl and the AIDS pandemic to the analysis of football match scores and testing theories about track positions in greyhound racing will help the reader to develop confidence in using the statistical method described.
Dr Mould presents an original and enlivening treatment of this subject which will prove valuable not only to medical science students but also to engineers, economists, and students from all the broad range of disciplines in which the techniques of statistical analysis are put into practice.
Introductory Medical Statistics aims to equip the reader with a useful working knowledge of statistics. Essential background material is covered first and the criteria for statistical significance are then discussed, followed by the various statistical tests leading on to the analysis of variance, the Wilcoxon rank sum test, the sign text, survival rate calculations, and regression and correlation. Real examples ranging from the aftermath of Chernobyl and the AIDS pandemic to the analysis of football match scores and testing theories about track positions in greyhound racing will help the reader to develop confidence in using the statistical method described.
Dr Mould presents an original and enlivening treatment of this subject which will prove valuable not only to medical science students but also to engineers, economists, and students from all the broad range of disciplines in which the techniques of statistical analysis are put into practice.
