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

More documents

Recommendations

Info

BIOMETRICSINFORMATIONIndex of Pamphlet Topics(for pamphlets #1 to #60) as of December, 2000Adjusted R-square18: Multiple regression: selecting the best subsetANCOVA: Analysis of Covariance13: ANCOVA: Analysis of Covariance31: ANCOVA: The linear models behind the F-testsANOVA: Analysis of Variance2: The importance of replication in analysis ofvariance3: ANOVA using SAS: specifying error terms4: ANOVA using SAS: How to pool error terms6: Using plot means for ANOVA9: Reading category variables with statisticssoftware14: ANOVA: Factorial designs with a separatecontrol16: ANOVA: Contrasts viewed as t-tests19: ANOVA: Approximate or Pseudo F-tests21: What are the degrees of freedom?22: ANOVA: Using a hand calculator to test a onewayANOVA23: ANOVA: Contrasts viewed as correlationcoefficients25: ANOVA: The within sums of squares as anaverage variance26: ANOVA: Equations for linear and quadraticcontrasts27: When the t-test and the F-test are equivalent28: Simple repression with replication: testing forlack of fit39: A repeated measures example40: Finding the expected mean squares and theproper error terms with SAS45: Calculating contrast F-tests when SAS will not48: ANOVA: Why a fixed effect is tested by itsinteraction with a random effect49: Power analysis and sample sizes for completelyrandomized designs with subsampling50: Power analysis and sample sizes for randomizedblock designs with subsampling51: Programs for power analysis/sample sizecalculations for CR and RB designs withsubsampling52: Post-hoc power analyses for ANOVA F-tests53: Balanced incomplete block (BIB) study designs54: Incomplete block designs: Connected designscan be analysed55: Displaying factor relationships in experiments56: The use of indicator variables in non-linearregression57: Interpreting main effects when a two-wayinteraction is present58: On the presentation of statistical results: asynthesis59: ANOVA: Coefficients for contrasts and meansof incomplete factorial designs60: MANOVA: Profile Analysis – an exampleusing SASASCII1: Producing ASCII files with SASBlocks17: What is the design?34: When are blocks pseudo-replicates?53: Balanced incomplete block (BIB) study designs54: Incomplete block designs: Connected designscan be analysedBonferroni13: ANCOVA: comparing adjusted meansBoxplots33: Box plotsChi-square Distribution15: Using SAS to obtain probability values for F-,t- and χ 2 statistics36: Contingency tables and log-linear models41Ministry of ForestsResearch Program
Cluster sampling43: Standard error formulas for cluster sampling(unequal cluster sizes)Completely Randomized Designs5: Understanding replication and pseudoreplication17: What is the design?48: ANOVA: Why a fixed effect is tested by itsinteraction with a random effect49: Power analysis and sample sizes for completelyrandomized designs with subsampling55: Displaying factor relationships in experiments57: Interpreting main effects when a two-wayinteraction is present59: ANOVA: Coefficients for contrasts and meansof incomplete factorial designsConfidence Intervals29: Simple Regression: Confidence intervals for apredicted X-value30: Interpretation of probability p-valuesConfidence Level11: Sample sizes: for one meanContingency Tables21: What are degrees of freedom?36: Contingency tables and log-linear models41: Power analysis and sample size determinationfor contingency table tests58: On the presentation of statistical results: asynthesisContrasts12: Determining polynomial contrast coefficients13: ANCOVA: comparing adjusted means14: ANOVA: Factorial designs with a separatecontrol16: ANOVA: Contrasts viewed as t-tests23: ANOVA: Contrasts viewed as correlationcoefficients26: ANOVA: Equations for linear and quadraticcontrasts45: Calculating contrast F-tests when SAS will not59: ANOVA: Coefficients for contrasts and meansof incomplete factorial designsControl14: ANOVA: Factorial designs with a separatecontrolCorrelation Coefficient23: ANOVA: Contrasts viewed as correlationcoefficientsCrossed Factors17: What is the design?48: ANOVA: Why a fixed effect is tested by itsinteraction with a random effect55: Displaying factor relationships in experiments57: Interpreting main effects when a two-wayinteraction is presentDegrees of Freedom19: ANOVA: Approximate or Pseudo F-tests21: What are degrees of freedom?Dunn-Bonferroni13: ANCOVA: comparing adjusted meansEDA (Exploratory Data Analysis)33: Box plotsError Bars38: Plotting error bars with SAS/GraphError Sums of Squares – see Residual sums ofsquares or Within sums of squaresError Terms3: ANOVA using SAS: specifying error terms4: ANOVA using SAS: How to pool error terms19: ANOVA: Approximate or Pseudo F-tests48: ANOVA: Why a fixed effect is tested by itsinteraction with a random effectExpected Mean Squares40: Finding the expected mean squares and theproper error terms with SAS422
Page 1 and 2: Stat-403/Stat-650 : Intermediate Sa
Page 3: Chapter 1Statistics - why the badim
Page 8 and 9: Problems With Using MicrosoftExcel
Page 10 and 11: The next example shows the help sup
Page 12 and 13: Knusel, Leo, “On the Accuracy of
Page 14 and 15: The latter tool is but one of many
Page 16 and 17: Is It Practical To Use Excel For St
Page 22 and 23: Using Excel for StatisticsStatistic
Page 24 and 25: Using Excel for StatisticsTipsWarni
Page 26 and 27: Using Excel for Statistics2. Adding
Page 28 and 29: Using Excel for StatisticsThe field
Page 30 and 31: Using Excel for StatisticsIn this e
Page 32 and 33: Using Excel for Statisticsbehaves l
Page 34 and 35: Using Excel for StatisticsThe resul
Page 36 and 37: Using Excel for Statisticsare liste
Page 38 and 39: DFID Guides Introduction PageStatis
Page 40 and 41: DFID Guides Introduction Pagetel: +
Page 44 and 45: Index of Pamphlet TopicsExperimenta
Page 46 and 47: Index of Pamphlet TopicsRegression2
Page 48 and 49: Chapter 6How do I interpret a p-val
Page 50 and 51: 2Type I error in the data exceeds w
Page 52 and 53: 4ssssssssssssssssssssssssssssssssss
Page 61 and 62: Chapter 8The Insignificance ofStati
Page 63 and 64: Statistical Signigicance TestingEco
Page 65 and 66: Statistical Signigicance TestingThe
Page 67 and 68: Statistical Significance Testingof
Page 69 and 70: Statistical Significance Testingapp
Page 71 and 72: Statistical Significance TestingBio
Page 73 and 74: Statistical Significance TestingThe
Page 75 and 76: Statistical Significance Testinginf
Page 77 and 78: Statistical Significance TestingHom
Page 79 and 80: Statistical Significance Testingsug
Page 81 and 82: Statistical Significance Testingres
Page 83 and 84: Statistical Significance TestingThe
Page 85 and 86: http://www.npwrc.usgs.gov/resource/
Page 87 and 88: http://www.npwrc.usgs.gov/resource/
Page 89: Chapter 9Designing EnvironmentalFie
Page 102 and 103:
101
Page 104 and 105:
103
Page 106 and 107:
105
Page 108 and 109:
107
Page 110 and 111:
109
Page 112 and 113:
Chapter 10Power analysis in wildlif
Page 114 and 115:
113
Page 116 and 117:
115
Page 118 and 119:
117
Page 120 and 121:
119
Page 122 and 123:
121
Page 124 and 125:
123
Page 126 and 127:
125
Page 128 and 129:
127
Page 130 and 131:
129
Page 132 and 133:
131
Page 134 and 135:
133
Page 136 and 137:
135
Page 138 and 139:
137
Page 140 and 141:
139
Page 142 and 143:
141
Page 144 and 145:
143
Page 146 and 147:
145
Page 148 and 149:
147
Page 150 and 151:
Chapter 12Pseudo-replication revisi
Page 152 and 153:
151
Page 154 and 155:
153
Page 156:
155
show all

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

Create successful ePaper yourself

Delete template?

Save as template?