Stat-403/Stat-650 : Intermediate Sampling and Experimental Design ...

Index of Pamphlet TopicsRegression21: What are degrees of freedom?27: When the t-test and the F-test are equivalent28: Simple regression with replication: testing forlack of fit29: Simple regression: Confidence intervals for apredicted X-value31: ANCOVA: The linear models behind the F-tests46: GLM Comparing regression lines56: The use of indicator variables in non-linearregression58: On the presentation of statistical results: asynthesisRepeated Measures32: Analysing a split-plot in time with the properrepeated measures ANOVA39: A repeated measures example58: On the presentation of statistical results: asynthesis60: MANOVA: Profile Analysis – an exampleusing SASReplication2: The importance of replication in analysis ofvariance5: Understanding replication and pseudoreplication17: What is the design?28: Simple regression with replication: testing forlack of fit48: ANOVA: Why a fixed effect is tested by itsinteraction with a random effectResidual Sums of Squares31: ANCOVA: The linear models behind the F-testsSample Size11: Sample sizes: for one mean41: Power analysis and sample size determinationfor contingency table tests49: Power analysis and sample sizes for completelyrandomized designs with subsampling50: Power analysis and sample sizes for randomizedblock designs with subsamplingSampling11: Sample sizes: for one mean43: Standard error formulas for cluster sampling(unequal cluster sizes)44: What do we look for in a working plan?Sampling Units17: What is the design?SAS Programs1: Producing ASCI files with SAS9: Reading category variables with statisticssoftware15: Using SAS to obtain probability values for F-,t-, and χ 2 statistics29: Simple Regression: Confidence intervals for apredicted X-value33: Box plots35: The computation of tree shadow lengths36: Contingency tables and log-linear models41: Power analysis and sample size determinationfor contingency table tests43: Standard error formulas for cluster sampling(unequal cluster sizes)47: SAS: Adding observations when class variables(e.g. species list) are missing51: Programs for power analysis/sample sizecalculations for CR and RB designs withsubsampling59: ANOVA: Coefficients for contrasts and meansof incomplete factorial designs60: MANOVA: Profile Analysis – an exampleusing SASSAS: CATMOD7: Logistic regression analysis: model statementsin PROC CATMOD36: Contingency tables and log-linear modelsSAS: Data Step20: Rearranging raw data files using SAS24: Reading WATFILE file into SAS47: SAS: Adding observations when class variables(e.g. species list) are missing455