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. |
Contents
Observations | 8 |
Probability | 36 |
Sampling from a Normal Distribution | 67 |
Copyright | |
23 other sections not shown
Common terms and phrases
adjusted analysis of variance appropriate binomial distribution chi-square column comparisons completely random design components compute confidence interval contrast correlation covariance cultivar data of Exercise data of Table degrees of freedom Dependent variable difference equation error mean square error rate estimate example expected value experiment experimental error experimental units experimentwise error rate F test F value Pr factor given H₁ homogeneity interaction Latin square linear main effects matrix measured multiple n₁ normal distribution null hypothesis number of observations obtained orthogonal Output P-value pairs parameters percent confidence interval plot population mean probability PROC GLM procedure random sample randomized complete block ratio Repeat Exercise replication residuals sample means SAS PROC significant square F value standard deviation standard error statistics sum of squares test criterion Test the null treatment means weight X₁ Y₁ zero σ² ΣΥ