Here are specific benchmark examples of how your company can put to use proven accommodation approaches that will have a positive impact on profitability, quality, and employee and customer relations. Case studies of some of America's leading corporations, including AT&T, Boeing, Federal Express, Bank of America, Digital Equipment, GE, IBM, Motorola, Wausau Insurance, Philip Morris, Texas Instruments, Marriott, Reynolds Metals, Sears, Roebuck, and many more. Key Features model for implementing the ADA; numerous case studies, both businesses and rehabilitation organizations; discussion of AIDS…mehr
Here are specific benchmark examples of how your company can put to use proven accommodation approaches that will have a positive impact on profitability, quality, and employee and customer relations. Case studies of some of America's leading corporations, including AT&T, Boeing, Federal Express, Bank of America, Digital Equipment, GE, IBM, Motorola, Wausau Insurance, Philip Morris, Texas Instruments, Marriott, Reynolds Metals, Sears, Roebuck, and many more. Key Features model for implementing the ADA; numerous case studies, both businesses and rehabilitation organizations; discussion of AIDS in the workplace; extensive examples and listing of access technologies in the workplace; ADA Supervisor's Guide and disability awareness information.
A: Placing Data in Context 1: Practical Data Analysis 2: Collaboration in Science 3: Experimental Design B: Working with Groups of Data 4: Group Summaries 5: Comparing Several Means 6: Multiple Comparisons of Means C: Sorting out Effects with Data 7: Factorial Designs 8: Balanced Experiments 9: Model Selection D: Dealing with Imbalance 10: Unbalanced Experiments 11: Missing Cells 12: Linear Models Inference E: Questioning Assumptions 13: Residual Plots 14: Comparisons with Unequal Variance 15: Getting Free from Assumptions F: Regressing with Factors 16: Ordered Groups 17: Parallel Lines 18: Multiple Responses G: Deciding on Fixed or Random Effects 19: Models with Random Effects 20: General Random Models 21: Mixed Effects Models H: Nesting Experimental Units 22: Nested Designs 23: Split Plot Design 24: General Nested Designs I: Repeating Measures on Subjects 25: Repeated Measures as Split Plot 26: Adjustments for Correlation 27: Cross-over Design
A: Placing Data in Context 1: Practical Data Analysis 2: Collaboration in Science 3: Experimental Design B: Working with Groups of Data 4: Group Summaries 5: Comparing Several Means 6: Multiple Comparisons of Means C: Sorting out Effects with Data 7: Factorial Designs 8: Balanced Experiments 9: Model Selection D: Dealing with Imbalance 10: Unbalanced Experiments 11: Missing Cells 12: Linear Models Inference E: Questioning Assumptions 13: Residual Plots 14: Comparisons with Unequal Variance 15: Getting Free from Assumptions F: Regressing with Factors 16: Ordered Groups 17: Parallel Lines 18: Multiple Responses G: Deciding on Fixed or Random Effects 19: Models with Random Effects 20: General Random Models 21: Mixed Effects Models H: Nesting Experimental Units 22: Nested Designs 23: Split Plot Design 24: General Nested Designs I: Repeating Measures on Subjects 25: Repeated Measures as Split Plot 26: Adjustments for Correlation 27: Cross-over Design
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