Stat-403/Stat-650 : Intermediate Sampling and Experimental Design ...
Stat-403/Stat-650 : Intermediate Sampling and Experimental Design ...
Stat-403/Stat-650 : Intermediate Sampling and Experimental Design ...
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MANOVA39: A repeated measures example60: MANOVA: Profile Analysis – an exampleusing SASMeans6: Using plot means for ANOVA11: Sample sizes: for one mean43: St<strong>and</strong>ard error formulas for cluster sampling(unequal cluster sizes)58: On the presentation of statistical results: asynthesis59: ANOVA: Coefficients for contrasts <strong>and</strong> meansof incomplete factorial designsMultiple Range Tests13: ANCOVA: comparing adjusted meansMultiple Regression8: St<strong>and</strong>ard errors for predicted values frommultiple regression18: Multiple regression: selecting the best subset27: When the t-test <strong>and</strong> the F-test are equivalent56: The use of indicator variables in non-linearregressionNon-linear Regression39: A repeated measures example56: The use of indicator variables in non-linearregressionPolynomial Contrasts12: Determining polynomial contrast coefficients26: ANOVA: Equations for linear <strong>and</strong> quadraticcontrasts32: Analysing a split-plot in time with the properrepeated measures ANOVAPower37: A general description of hypothesis testing <strong>and</strong>power analysis41: Power analysis <strong>and</strong> sample size determinationfor contingency table tests49: Power analysis <strong>and</strong> sample sizes for completelyr<strong>and</strong>omized designs with subsampling50: Power analysis <strong>and</strong> sample sizes for r<strong>and</strong>omizedblock designs with subsampling51: Programs for power analysis/sample sizecalculations for CR <strong>and</strong> RB designs withsubsampling52: Post-hoc power analyses for ANOVA F-testsPredicted values8: St<strong>and</strong>ard errors for predicted values frommultiple regression29: Simple Regression: Confidence intervals for apredicted X-valueProbability values15: Using SAS to obtain probability values for F-,t-, <strong>and</strong> χ 2 statistics30: Interpretation of probability p-valuesApproximate or Pseudo F-tests19: ANOVA: Approximate or Pseudo F-testsPseudo-Replication5: Underst<strong>and</strong>ing replication <strong>and</strong> pseudoreplication34: When are blocks pseudo-replicates?Questionnaire10: Results of biometrics questionnaireR-square18: Multiple regression: selecting the best subsetR<strong>and</strong>om Factors40: Finding the expected mean squares <strong>and</strong> theproper error terms with SAS48: ANOVA: Why a fixed effect is tested by itsinteraction with a r<strong>and</strong>om effectR<strong>and</strong>omized Block <strong>Design</strong>s5: Underst<strong>and</strong>ing replication <strong>and</strong> pseudoreplication17: What is the design?34: When are blocks of pseudo-replicates?50: Power analysis <strong>and</strong> sample sizes for r<strong>and</strong>omizedblock designs with subsampling55: Displaying factor relationships in experiments444
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