Read more
Zusatztext "? guides readers to think through their problems! to design experiments to answer their questions! to analyze the data accruing from those experiments! and to draw sensible inferences. ? the exercises at the end of the chapter give readers the opportunity to test their understanding. ? a handy companion for agronomists and environmental scientists who need to experiment with treatments they can control."-R. Webster! Journal of Environmental Quality! Vol. 36! Issue 1! January-February 2007 "?One strength of the text is that there are many actual agricultural and biological examples and data analysis problems. ? This text would be beneficial to those whose backgrounds are in agriculture and biology! those who would like to see basic computational details! and those who prefer the classical test statistic/critical value approach to hypothesis testing."-Biometrics! December 2006 Informationen zum Autor Reza Hoshmand (Author) Klappentext Useful as a text or reference! this book presents various experimental designs! reasons for selecting each design! and statistical analysis. This second edition features a new chapter on covariance analysis to help readers understand how to reduce the error associated with an experiment and examine covariances among selected variables. It includes expanded material on multiple regression analysis! ANOVA! and ANCOVA. It also provides additional examples! problems! case studies! a solutions manual! and a Minitab guide at the end of several chapters to assist in data analysis. This text remains an ideal introduction to designing experiments in agriculture! environmental science! and natural sciences. Zusammenfassung An introductory guide to experimental design and analysis that provides an understanding of the logical underpinnings of design and analysis by selecting and discussing only those carefully chosen designs that offer the greatest utility. Inhaltsverzeichnis THE NATURE OF AGRICULTURAL RESEARCH Fundamental ConceptsResearch by Practitioners KEY ASSUMPTIONS OF EXPERIMENTAL DESIGNSIntroductionAssumptions of the Analysis of Variance (ANOVA) and Their ViolationsMeasures to Detect Failures of the Assumptions Data Transformation DESIGNS FOR REDUCING ERRORIntroductionApproaches to Eliminating Uncontrolled Variations Error Elimination by Several Groupings of Units SINGLE-FACTOR EXPERIMENTAL DESIGNSIntroductionComplete Block Designs Incomplete Block DesignsTWO-FACTOR EXPERIMENTAL DESIGNSFactorial Experiments Main Effects and Interactions in a Two-Factor ExperimentInterpretation of Interactions Factorials in Complete Block Designs Split-Plot or Nested Designs Strip-Plot DesignTHREE (OR MORE)-FACTOR EXPERIMENTAL DESIGNS IntroductionSplit-Split-Plot Design Strip-Split-Plot Design Factorial Experiments in Fractional Replication TREATMENT MEANS COMPARISONS IntroductionComparisons of Paired Means Comparisons of Grouped MeansSAMPLE DESIGNS OVER TIME Terminology and ConceptsAnalysis of Experiments over YearsAnalysis of Experiments over Seasons REGRESSION AND CORRELATION ANALYSIS Bivariate Relationships Regression Analysis Correlational Analysis Curvilinear Regression AnalysisMultiple Regression and CorrelationCOVARIANCE ANALYSISIntroductionCovariance Analysis ProceduresEstimating Missing Data Appendix A: Chi-Square Distribution Appendix B: The Arc SineTransformationAppendix C: Selected Latin SquaresAppendix D: Random Digits Appendix E: Points for the Distribution of FAppendix F: Basic Plans for Balanced and Partially Balanced Lattice DesignsAppendix G: Fractional Factorial Design PlansAppendix H: Significant Studentized Ranges for 5% and 1% Level New Multiple Range TestAppendix I: Student t Distribution Appendix J: Coefficients and the Sum of Squares of Sets of Orthogonal Polynomials When There Are Equal Interval TreatmentsAppendix K: MinitabIndex ...
