Table of Contents
Two Factors Full Factorial Design without Replications
Overview
Two Factors Full Factorial Design
Model
Computation of Effects
Estimating Experimental Errors
Analysis of Variance
ANOVA Table
Confidence Intervals For Effects
Case Study 21.1: Cache Design Alternatives
Multiplicative Models
Case Study 21.2: RISC architectures
Cache Study 21.2: Simulation Results
Case Study 21.2: Multiplicative Model
Case Study 21.2: Confidence Intervals
Cache Study 21.2: Visual Tests
Case Study 21.2: ANOVA
Case Study 21.3: Processors
Case Study 21.3: Additive Model
Case Study 21.3: Multiplicative Model
Case Study 21.3: Intel iAPX 432
Case Study 21.3: ANOVA with Log
Case Study 21.3: Confidence intervals
Missing Observations
Case Study 21.4: RISC-I Execution Times
Case Study 21.5: Using Multiplicative Model
Case Study 21.5: Experimental Errors
Case Study 21.5: CIs for Processor Effects
Case Study 21.5: Visual Tests
Case Study 21.5: Analysis without 68000
Case Study 21.5: RISC-I Code Size
Case Study 21.5: Confidence Intervals
Summary
Exercise 21.1
Exercise 21.2
Exercise 21.3
Exercise 21.4 |