JMP_DOE官方使用教程.pdfSAS(全球最大的统计学软件公司)推出的一种交互式可视化统计发现软

文件名称: JMP_DOE官方使用教程.pdf

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详细说明：SAS(全球最大的统计学软件公司)推出的一种交互式可视化统计发现软件系列，包括JMP，JMP Pro，JMP Clinical，JMP Genomics，SAS Simulation Studio for JMP等强大的产品线。主要用于实现统计分析。JMP在SAS的基础上形成了自己的算法，特别强调以统计方法的实际应用为导向，交互性、可视化能力强，使用方便，尤其适合非统计专业背景的数据分析人员使用，在同类软件中有较大的优势。Get the most from JMP Whcther you arc a first-timc or a long-timc uscr, therc is always something to learn about JMP isit JMP. com to find the following live and recorded Webcasts about how to get started with jMp vidco demos and Webcasts of ncw fcaturcs and advanccd tcchniqucs schedules for seminars being held in your area success stories showing how others use JMP a blog with tips, trickS, and stories from J MP staff a forum to discuss jMp with other users http://www.imp.com/getstarted Contents Design of Experiments 1 Introduction to Designing Experiments A Beginner's Tutorial ......... I About Designing Experiments rimcnt 3 The Situation · Step 1: Design the Experiment Step 2: Define Factor Constraints Step 3: Add Interaction Terms Step 4: Determine the Number of runs Step 6: Gather and Enter the data Step 7: Ar the results 2 Examples Using the Custom Designer Creating Screening Experiments Creating a Main-Effects-Only Screening Design .......... 17 Creating a Screening Design to Fit All Two-Factor Interactions A Compromise design between main Effects only and all interactions 2I Creating Super Screening Designs ·· Screening Designs with Flexible block Sizes 27 Checking for Curvature Using One Extra Run 3I Creating response Surface Experiments 4 Exploring the prediction Variance Surface ng -oOp Designs for Response surface model A Three-Factor Response Surface design Response Surface with a blocking factor Creating mixture experiments ture Factors Experiments that are mixtures of Mixtures 48 11 Special-Purpose Uses of the Custom Designer Designing Experiments with Fixed Covariate Factors Creating a Design with Two Hard-to-Change Factors: Split Plot 55 Technical Discussion 6 3 Building Custom Designs The Basic Steps Crcating a Custom Dcsign∴… Enter Responses and Factors into the Custom designer Describe the model Specifying Alias Terms 70 Select the number of ru aderstandin Design evaluation 72 Specify Output Options Make the jmp Design table ··· Creating Random Block Designs… Creating Split Plot designs Creating Split-Split Plot Designs Crcating Strip Plot designs.∴…,,,,,,…….82 Special Custom Design Command 8 Save responses and save factors Load Responses and load factors · 8 Save Constraints and Load constraints 8 Set random Seed: Setting the Number generator 8 Simulate responses 86 Savc X Matrix: Vicwing thc Numbcr of Rows in the Moments Matrix and thc Dcsign Matrix(X)in thc g Optimality Criterion ,,,,,88 umber of Starts: Changing the Number of Random Starts 88 Sphere radius: Constraining a Design to a Hypersphere Disallowed Combinations: Accounting for factor Level restrictions Advanced Options for the Custom Designer 9I Save script to script window Assigning Colunn Properties 单着 Define Low and High Values(DOE Coding) for Columns 94 Sct columns as Factors for Mixture Experiments Define Response Column Values Assign Columns a Design role Identify Factor Changes Column Property How Custom Designs Work: behind the scenes 4 Screening designs IOT Screening Design Examples∴… Io3 USing Two Continuous Factors and Onc Categorical Fa actor Io3 Using Five Continuous Factors IO Creating a Screening design 09 Enter Responses ........... ·············· 109 Enter factors Choose a design ...,,.III Display and Modify a Design IS Specify Output Options……… View the Design Table I20 Create a Plackett-Burman design I20 Analysis of Screening data Using the screening analysis Platform Using the Fit model platform.............. 5 Response Surface Designs 27 A Box-Behnken Design: The Tennis Ball Example I29 The Prediction profiler I32 A Response Surface plot( Contour Profiler) I34 Geometry of a box-Behnken Design ..I36 Creating a response surface design I36 Enter Res d factors I37 Choose a desig I38 ify Output options Ⅴ iew the Design table 140 6 Full Factorial Designs The Five-Factor Reactor Example Analyze the reactor data Creating a Factorial Design IfI Enter Responses and Factors ISI ct Output op I52 Makc thc tablc I52 7 Mixture Designs 155 Mixture Design ty The Optimal Mixture design I57 The Simplex Centroid Design retin I59 Simplex Centroid Design Examples I6 The Simplex lattice Design The extreme vertices Design ··* Creating the design∴ I64 An extreme Vertices Example with Range Constraints An Extreme vertices Example with Linear Constraints I66 Extreme Vertices Method: How It Works ,,,,I6 The ABCD Design· Creating Ternary Plots 68 Fitting Mixture Designs Whole Model Tests and Analysis of Variance Reports I7I Undcrstanding Rcsponsc Surfacc Rcports A Chemical mixture Example IZI Create the Design Analyze the mixture Model ......... I74 The Prediction profiler he mixture profiler I7 A Ternary Plot of the Mixture Response Surface 8 Discrete Choice Designs Introduction Create an Example choice Experiment ··, Analyze the Example Choice Experiment I86 D esign a Choice Experiment Using Prior Information Administer the survey and analyze results Initial Choice Platform Analysis I 9I Find Unit Cost and Trade Off Costs with the Profiler 92 9 Space-Filling Designs I95 Introduction to Space-Filling Designs .I97 Sphere-Packing Designs ..... Crcating a Sphcrc-Packing dcsign 97 Visualizing the Sphere-Packing Design Latin Hypercube designs · 200 Creating a Latin Hypercube design ·············· sualizin e Latin Hypercube Design Uniform Designs 204 Comparing Sphere-Packing, Latin Hypercube, and Uniform Methods 06 Minimum Potential designs Maximum Entropy designs∴.…∴ ·· 209 Gaussian Process Imse Optimal Designs LI Borehole Model: A Sphere-Packing Example Create the Sphere-Packing Design for the borehole Data 2I2 Guidelines for the analysis of Deterministic Data Results of the borehole experiment 13 10 Accelerated Life Test Designs Designing Experiments for Accelerated Life Tests 2I Overview of Accelerated Life Test Designs 219 Using the alt design Platform 219 atform Op 11 Nonlinear Designs camp oles of nonlinear d 23I Using nonlinear Fit to Find prior Parameter Estimates Creating a nonlinear Design with No Prior dat Crcating a Nonlincar dcsign .... 24I Identify the response and Factor Column with Formula Set up Factors and parameters in the nonlinear Design dialo 242 Enter the Number of Runs and Preview the Design 243 Makc tablc or augment the table Advanced Options for the nonlinear designer 45 12 Taguchi Designs 247 The Taguchi Design Approach 249 Taguchi Design Example Analyze the data 252 reating a taguchi Design 254 il the response and Add factors 254 Choose inner and Outer array designs Display coded design Make the design Table 13 Augmented Designs 2 A D-Optimal Augmentation of the Reactor Example 26I nalyzc thc Augmcntc esign 264 Creating an Augmented design 27I Replicate a 272 Add center points Creating a Foldover Design 276 Adding Axial Points Adding New Runs and Terms Special augment Design Commands Save the Design(X) matrix ·· 282 Modify the Design Criterion(D-or /-Optimality) 282 Select the Number of random starts 28 Specify the Sphere radius value∴… 28 Disallow Factor combinations 4 14 Prospective sample size and Power Launching the sample size and power Platform ..287 One-Sample and Two-Sample means Single-sample mean

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