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Chapter 61: The REG Procedure
Figure 61.1: ANOVA Table
Figure 61.2: Parameter Estimates
Figure 61.3: Plot of Residual vs. Predicted Values
Figure 61.43: Regression Using the INFLUENCE Option
Figure 61.57: Regression Using DW Option
Figure 61.4: ANOVA Table and Parameter Estimates
Figure 61.5: Confidence Limits
Figure 61.6: Residual Analysis
Figure 61.7: Plot of Residual vs. Predicted Values
Figure 61.8: ANOVA Table and Parameter Estimates
Figure 61.9: Confidence Limits and Residual Analysis
Figure 61.10: Plot of Residual vs. Predicted Values
Figure 61.11: Plot of Population vs Year with Confidence Limits
Figure 61.12: TYPE=CORR Data Set Created by PROC CORR
Figure 61.13: Regression on TYPE=CORR Data Set
Figure 61.14: TYPE=SSCP Data Set Created by PROC CORR
Figure 61.15: Regression on TYPE=SSCP Data Set
Figure 61.16: Regression Output for Model M1
Figure 61.17: Regression Output for Model M2
Figure 61.18: OUTEST= Data Set
Figure 61.19: The OUTEST= Data Set When TABLEOUT is Specified
Figure 61.20: PROC REG Output for Physical Fitness Data: Best Models
Figure 61.21: PROC PRINT Output for Physical Fitness Data: OUTEST= Data Set
Figure 61.22: SSCP Data Set Created with OUTSSCP= Option: REG Procedure
Figure 61.23: Interactive Analysis: Full Model
Figure 61.24: Interactive Analysis: Reduced Model
Figure 61.25: Interactive Analysis: Scatter Plot
Figure 61.26: Interactive Analysis: Scatter Plot for Refitted Model
Figure 61.28: SS1, SS2, STB, CLB, COVB, and CORRB Options: Parameter Estimates
Figure 61.27: ANOVA Table
Figure 61.29: SS1, SS2, STB, CLB, COVB, and CORRB Options: Covariances and Correlations
Figure 61.30: Regression Using the R, CLI, and CLM Options
Figure 61.31: Regression Using the R, CLI, and CLM Options
Figure 61.32: Scatter Plot Showing Data, Predicted Values, and Confidence Limits
Figure 61.33: Collecting Residual Plots for the Full Model
Figure 61.34: Overlaid Residual Plots for Full and Reduced Models
Figure 61.35: Residual Plot for Reduced Model Only
Figure 61.36: Side-by-Side Residual Plots for the Full and Reduced Models
Figure 61.37: Plotting Studentized Residuals Against Predicted Values
Figure 61.38: Painting One Observation
Figure 61.39: Painting Several Observations
Figure 61.40: Painting Observations on More than One Plot
Figure 61.41: Model That Is Not Full Rank: REG Procedure
Figure 61.42: Regression Using the TOL, VIF, and COLLIN Options
Figure 61.44: Partial Regression Leverage Plots (Experimental)
Figure 61.45: Partial Regression Leverage Plots
Figure 61.46: Full Model for CLASS Data, Residuals Shown
Figure 61.47: Model with Reweighted Observations
Figure 61.48: Observations Excluded from Analysis, Model Refitted and Observations Reweighted
Figure 61.49: Restoring Weights of All Observations
Figure 61.50: Example of UNDO in REWEIGHT Statement
Figure 61.51: REWEIGHT Statement with RESET option
Figure 61.52: Multivariate Analysis of Variance: REG Procedure
Figure 61.53: Multivariate Analysis of Variance: REG Procedure
Figure 61.54: Multivariate Analysis of Variance: First Test
Figure 61.55: Multivariate Analysis of Variance: Second Test
Figure 61.56: Multivariate Analysis of Variance: Second Test
Chapter 62: The ROBUSTREG Procedure
Figure 62.1: Model Fitting Information and Summary Statistics
Figure 62.2: Model Parameter Estimates
Figure 62.3: Diagnostics
Figure 62.4: RDPLOT for Stackloss Data (Experimental)
Figure 62.5: DDPLOT for Stackloss Data (Experimental)
Figure 62.6: Histogram (Experimental)
Figure 62.7: Q-Q PLOT (Experimental)
Figure 62.8: Goodness-of-Fit
Figure 62.9: Test of Significance
Figure 62.10: Model Parameter Estimates
Figure 62.11: Diagnostics
Figure 62.12: Model Fitting Information and Summary Statistics
Figure 62.13: LTS Profile
Figure 62.14: LTS Parameter Estimates
Figure 62.15: Diagnostics
Figure 62.16: Final Weighted LS Estimates
Chapter 63: The RSREG Procedure
Figure 63.1: Summary Statistics and Analysis of Variance
Figure 63.2: Parameter Estimates and Hypothesis Tests
Figure 63.3: Canonical Analysis and Eigenvectors
Figure 63.4: The Response Surface Obtained from the PREDICT Option
Figure 63.5: Top Five Predictions
Chapter 64: The SCORE Procedure
Figure 64.1: Views of the Scores, Schools, and New Data Sets
Figure 64.2: Bar Chart of School Type
Chapter 65: The SIM2D Procedure
Figure 65.1: Locations of Measured Samples
Figure 65.2: Surface Plot of Coal Seam Thickness
Figure 65.3: Simulation Statistics at Grid Point (XC=0, YC=0)
Figure 65.4: Simulation Statistics at Grid Point (XC=75, YC=75)
Chapter 66: The STDIZE Procedure
Figure 66.1: Schematic Plots from PROC UNIVARIATE
Figure 66.2: Table for Extreme Observations When Type=urban
Figure 66.3: Location and Scale Measures Table When METHOD=STD
Figure 66.4: Location and Scale Measures Table When METHOD=MAD
Figure 66.5: Location and Scale Measures Table When METHOD=IQR
Figure 66.6: Location and Scale Measures Table When METHOD=ABW
Figure 66.7: After Deleting the Outlier, Location and Scale Measures Table When METHOD=STD
Chapter 67: The STEPDISC Procedure
Figure 67.1: Summary Information
Figure 67.2: Step 1: Variable HEIGHT Selected for Entry
Figure 67.3: Step 2: No Variable is Removed; Variable Length1 Added
Figure 67.4: Step 7: No Variables Entered or Removed
Figure 67.5: Step Summary
Chapter 68: The SURVEYFREQ Procedure
Figure 68.1: SIS_Survey Data Summary
Figure 68.2: One-Way Table of Response
Figure 68.3: Confidence Limits for Response Percentages
Figure 68.4: Chi-Square Goodness-of-Fit Test for Response
Figure 68.5: Two-Way Table of SchoolType by Response
Figure 68.6: Two-Way Table with Row Percentages
Figure 68.7: Chi-Square Test of No Association
Chapter 69: The SURVEYLOGISTIC Procedure
Figure 69.1: Stratified PPS Sample (First 10 Observations)
Figure 69.2: Stratified PPS Sample, Model Information
Figure 69.3: Stratified PPS Sample, Number of Observations
Figure 69.4: Stratified PPS Sample, Response Profile
Figure 69.5: Stratified PPS Sample, Stratification Summary
Figure 69.6: Stratified PPS Sample, Testing the Proportional Odds Assumption
Figure 69.7: Stratified PPS Sample, Model Fitting Information
Figure 69.8: Stratified PPS Sample, Testing Global Null Hypothesis
Figure 69.9: Stratified PPS Sample, Parameter Estimates
Figure 69.10: Stratified PPS Sample, Odds Ratios
Chapter 70: The SURVEYMEANS Procedure
Figure 70.1: Analysis of Ice Cream Spending, Simple Random Sample Design
Figure 70.2: Data Summary
Figure 70.3: Stratum Information
Figure 70.4: Analysis of Ice Cream Spending, Stratified SRS Design
Figure 70.5: The Data Set MyStat
Figure 70.6: Rectangular Structure in the Output Data Set
Figure 70.7: Stacking Structure in the Output Data Set
Figure 70.8: Degrees of Freedoms in Domain Analysis
Chapter 71: The SURVEYREG Procedure
Figure 71.1: Summary of Data
Figure 71.2: Testing Effects in the Regression
Figure 71.3: Regression Coefficients
Figure 71.4: Summary of the Regression
Figure 71.5: Stratification and Classification Information
Figure 71.6: Testing Effects
Figure 71.7: Regression Coefficients
Figure 71.8: The Data Set MyParmEst
Chapter 72: The SURVEYSELECT Procedure
Figure 72.1: Customers Data Set (First 10 Observations)
Figure 72.2: Sample Selection Summary
Figure 72.3: Customer Sample (First 20 Observations)
Figure 72.4: Stratification of Customers by State and Type
Figure 72.5: Sample Selection Summary
Figure 72.6: Customer Sample (First 30 Observations)
Figure 72.7: Sample Selection Summary
Chapter 74: The TPSPLINE Procedure
Figure 74.1: Plot of Data Set MEASURE
Figure 74.3: Data Set ESTIMATE
Figure 74.4: Plot of TPSPLINE Fit of Data Set Measure
Figure 74.5: Plot of TPSPLINE fit
Figure 74.5: Plot of TPSPLINE fit
Figure 74.2: Output from PROC TPSPLINE
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SAS.STAT 9.1 Users Guide (Vol. 6)
ISBN: N/A
EAN: N/A
Year: 2004
Pages: 127
BUY ON AMAZON
Agile Project Management: Creating Innovative Products (2nd Edition)
Thriving in a Chaordic World
Phase: Explore
Agile Practices
Envision Summary
Scope Evolution
Software Configuration Management
A Practical Approach to Documentation and Configuration Status Accounting
A Practical Approach to Configuration Verification and Audit
Configuration Management and Software Engineering Standards Reference
Appendix C Sample Data Dictionary
Appendix V Functional Configuration Audit (FCA) Checklist
A+ Fast Pass
Domain 4 Motherboard/Processors/Memory
Domain 5 Printers
Domain 1 Operating System Fundamentals
Domain 3 Diagnosing and Troubleshooting
Domain 4 Networks
Visual C# 2005 How to Program (2nd Edition)
Exercises
Wrap-Up
Wrap-Up
Case Study: Secure Books Database Application
G.9. frameset Element
After Effects and Photoshop: Animation and Production Effects for DV and Film, Second Edition
Rotoscoping Techniques with Photoshop
Motion Matte Painting in Photoshop
Color, Light, and Focus
Custom Scene Transitions
Appendix Adobe Photoshop and After Effects Resources
Programming .Net Windows Applications
Web Applications Versus Windows Applications
PictureBox
Class Hierarchy
Menus and Bars
Multiuser Updates
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