Biostatistical AnalysisPresents a broad collection of data analysis techniques suitable for biological investigations, either as an introductory textbook assuming no prior knowledge of statistics, or as a reference on concepts and procedures of statistical analysis for professional use in the biological disciplines. Each |
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Page vii
... Nonparametric Testing 585 Exercises 588 25 CIRCULAR DISTRIBUTIONS : DESCRIPTIVE STATISTICS 25.1 Data on a Circular Scale 591 25.2 Graphical Presentation of Circular Data 594 25.3 Sines and Cosines of Circular Data 596 25.4 The Mean ...
... Nonparametric Testing 585 Exercises 588 25 CIRCULAR DISTRIBUTIONS : DESCRIPTIVE STATISTICS 25.1 Data on a Circular Scale 591 25.2 Graphical Presentation of Circular Data 594 25.3 Sines and Cosines of Circular Data 596 25.4 The Mean ...
Page 147
... nonparametric approach is applicable , then the former will always be more powerful than the latter ( i.e. , the nonparametric method will have a greater probability of committing a Type II error ) . Often the difference in power is not ...
... nonparametric approach is applicable , then the former will always be more powerful than the latter ( i.e. , the nonparametric method will have a greater probability of committing a Type II error ) . Often the difference in power is not ...
Page
... nonparametric , 390 , 392 partial , 422 of Friedman's nonparametric two - factor ANOVA , 267 of Kolmogorov - Smirnov goodness of fit , 474 , 476 of Kruskal - Wallis nonparametric ANOVA , 198 in McNemar test , 173 of Mann - Whitney two ...
... nonparametric , 390 , 392 partial , 422 of Friedman's nonparametric two - factor ANOVA , 267 of Kolmogorov - Smirnov goodness of fit , 474 , 476 of Kruskal - Wallis nonparametric ANOVA , 198 in McNemar test , 173 of Mann - Whitney two ...
Contents
POPULATIONS AND SAMPLES | 15 |
MEASURES OF DISPERSION AND VARIABILITY | 31 |
Exercises | 62 |
Copyright | |
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analysis of variance ANOVA Appendix Table b₁ b₂ binomial distribution binomial test calculated cell Chapter chi-square confidence interval confidence limits cont contingency table correlation coefficient Critical Values data of Example degrees of freedom demonstrated in Example determine diets difference Distribution Numerator employed equal Equation estimate exact test experimental design Fisher groups hypothesis test interaction levels of factor linear males Mann-Whitney test mean square measurements median mg/m³ Mmmmm multiple comparison multiple regression n₁ nonparametric normal approximation normal distribution null hypothesis number of data observed obtained one-tailed test parameter population mean probability procedure proportion R₁ random ranks ratio regression coefficients reject reject Ho residual sample sizes sampled population shown in Example significance species standard error sum of squares TABLE B.4 test statistic total number transformation two-sample Type I error v₁ weight X₁ zero ΣΧ