Principles and Procedures of Statistics: A Biometrical ApproachObservations; Probability; Sampling from a normal distribution; Comparisons involving two sample means; Principles of experimental design; Analysis of variance I: the one-way classification; Multiple comparisons; Analysis of variance II: multiway classifications; Linear regression; Linear correlation; Matrix notation; Linear regression in matrix notation; Multiple and partial regression and correlation; Analysis of variance III: factorial experiments; Analysis of variance IV: split-plot designs and analysis; Analysis of covariance; Analysis of variance V: unequal subclass numbers; Curve fitting; Some uses of Chi square; Enumeration Data I: one-way classifications; Enumeration Data II: contingency tables; Some discrete distributions; Nonparametric statistics; Sampling finite populations. |
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alternative analysis of variance apply appropriate approximately average B₁ b₂ binomial distribution Chap column common comparisons complete block design completely random design compute confidence interval correlation covariance data of Exercise data of Table degrees of freedom differences equation error rate estimate of o² example experiment experimental error experimental units factor factorial experiment frequency given H₁ homogeneity independent interaction Latin square linear main effects matrix measure multiple n₁ n₂ normal distribution null hypothesis number of observations number of replicates number of treatments obtained pairs parameter percent confidence interval plants plots population mean possible precision probability procedure random sample randomized complete block ratio regression coefficients Repeat Exercise residual sample means significant sources of variation standard deviation statistics sum of squares tabulated test criterion Test the null tion weight X₁ Y₁ Y₂ Z₁ zero μ₁ σ² ΣΥ