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 249
... number of females + number of males 237.0+ 199.5 10+ 10 = 21.82 mg / 100 ml $ 2 95 % CI for Up = X , ± 0.05 ( 2 ) ... data in the cell in row i and column j is nij ( number of data in row i ) ( number of data in column j ) N ( 12.21 ) ...
... number of females + number of males 237.0+ 199.5 10+ 10 = 21.82 mg / 100 ml $ 2 95 % CI for Up = X , ± 0.05 ( 2 ) ... data in the cell in row i and column j is nij ( number of data in row i ) ( number of data in column j ) N ( 12.21 ) ...
Page 252
... data in level j of factor B , EEE Xij is the sum of all the known data , and N is the total number of data ( including the missing datum ) in the experimental design . For example , if datum X124 had been missing in Example 12.1 , it ...
... data in level j of factor B , EEE Xij is the sum of all the known data , and N is the total number of data ( including the missing datum ) in the experimental design . For example , if datum X124 had been missing in Example 12.1 , it ...
Page 302
... data in level j of factor B , etc .; the summation of a A¡ + bB ; + cC¡ + ... is over all factors ; k is the number of factors ; X is the sum of all the other data in all levels of all factors ; and N is the total number of data ...
... data in level j of factor B , etc .; the summation of a A¡ + bB ; + cC¡ + ... is over all factors ; k is the number of factors ; X is the sum of all the other data in all levels of all factors ; and N is the total number of data ...
Contents
POPULATIONS AND SAMPLES | 15 |
MEASURES OF DISPERSION AND VARIABILITY | 31 |
Exercises | 62 |
Copyright | |
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Common terms and phrases
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