## Principles and Procedures of Statistics: A Biometrical ApproachThis textbook provides a thorough treatment of major statistical methods and techniques for both staticticians and non-statisticians requiring a foundation in applied statistics. There is an emphasis throughout on inference from data, the principle of fitting models by least squares, and careful interpretation of results. The authors employ SAS to produce PC-based statistical graphics and perform some analyses where appropriate. This edition includes updated real-world data sets. |

### Common terms and phrases

95 percent confidence adjusted alternative analysis of variance appropriate binomial coefficient column comparisons complete block design completely random design components computed confidence interval contrast correlation covariance critical value cultivar data of Exercise data of Table degrees of freedom differences equation error mean square error rate example experiment experimental error experimental units experimentwise error rate F test F value Pr given H₁ homogeneity interaction intercept Latin square likelihood linear matrix measure multiple n₁ normal distribution null hypothesis number of observations obtained orthogonal Output P-value pairs parameter percent confidence interval plants plot population mean pots probability procedure random sample randomized complete block ratio Repeat Exercise residuals sample means significant sources of variation square F value standard deviation standard error statistics sum of squares test criterion Test the null transformation treatment means true weight X₁ Y₁ zero σ² ΣΥ