Jmp Start Statistics: A Guide to Statistics and Data Analysis Using Jmp, Sixth Edition

Contents......Page 3
Preface......Page 15
…on your own with JMP Help......Page 20
…reading about JMP......Page 21
Chapter Organization......Page 22
Typographical Conventions......Page 24
Hello!......Page 26
The JMP Starter (Macintosh)......Page 28
The JMP Home Window (Windows)......Page 29
Open a JMP Data Table......Page 31
Launch an Analysis Platform......Page 33
Interact with the Report Surface......Page 34
Special Tools......Page 37
Customize JMP......Page 38
Modeling Type......Page 40
Navigating Platforms and Building Context......Page 41
Contexts for the t-Test......Page 42
Contexts for Nonparametric Statistics......Page 43
The Personality of JMP......Page 44
Overview......Page 46
The Ins and Outs of a JMP Data Table......Page 48
Mousing around a Data Table: Cursor Forms......Page 49
Creating a New JMP Table......Page 51
Define Rows and Columns......Page 52
Enter Data......Page 54
The New Column Command......Page 55
Plot the Data......Page 56
Importing Data......Page 58
Importing Text Files......Page 60
Importing Other File Types......Page 63
Copy, Paste, and Drag Data......Page 65
Moving Data Out of JMP......Page 66
Copy and Paste......Page 67
Create Interactive Web Reports......Page 68
Pop-up Menu Commands......Page 69
Data Management......Page 70
Give New Shape to a Table: Stack Columns......Page 71
Create Summary Statistics with the Summary Command......Page 74
Create Summary Statistics with Tabulate......Page 77
Running Data Table Scripts......Page 79
Opening and Running Stand-alone Scripts......Page 80
Overview......Page 82
The Formula Editor Window......Page 84
The Formula Editor and the JMP Scripting Language......Page 85
A Quick Example: Standardizing Data......Page 86
Making a New Formula Column......Page 88
Using Popular Formula Functions......Page 90
Writing Conditional Expressions......Page 91
Summarizing Data with the Formula Editor......Page 96
Generating Random Data......Page 101
Local Variables and Table Variables......Page 106
Working with Dates......Page 108
Cutting, Dragging, and Pasting Formulas......Page 109
Exercises......Page 110
Overview......Page 114
The Yin and Yang of Statistics......Page 116
The Faces of Statistics......Page 117
Don’t Panic......Page 118
Three Levels of Uncertainty......Page 120
Assumptions......Page 121
Data Mining?......Page 122
Statistical Terms......Page 123
Overview......Page 127
Rolling Dice......Page 129
Flipping Coins, Sampling Candy, or Drawing Marbles......Page 132
Probability of Making a Triangle......Page 133
Confidence Intervals......Page 138
Data Table-Based Simulations......Page 139
Other JMP Simulators......Page 140
Exercises......Page 141
Overview......Page 143
Looking at Distributions......Page 146
Probability Distributions......Page 148
True Distribution Function or Real-World Sample Distribution......Page 149
The Normal Distribution......Page 151
Generating Random Data......Page 152
Histograms......Page 153
Stem-and-Leaf Plots......Page 155
Dot Plots......Page 156
Outlier and Quantile Box Plots......Page 157
Mean and Standard Deviation......Page 159
Mean versus Median......Page 160
Extremes, Tail Detail......Page 161
Confidence Intervals for the Mean......Page 162
Testing Hypotheses: Terminology......Page 165
The Normal z-Test for the Mean......Page 167
Case Study: The Earth’s Ecliptic......Page 168
Student’s t-Test......Page 170
Comparing the Normal and Student’s t Distributions......Page 171
Testing the Mean......Page 172
The p-Value Animation......Page 173
Power of the t-Test......Page 175
Practical Significance versus Statistical Significance......Page 177
Examining for Normality......Page 179
Normal Quantile Plots......Page 180
Statistical Tests for Normality......Page 183
Special Topic: Practical Difference......Page 185
Special Topic: Simulating the Central Limit Theorem......Page 188
Seeing Kernel Density Estimates......Page 190
Exercises......Page 191
Overview......Page 194
When the Difference Isn’t Significant......Page 196
Check the Data......Page 197
Launch the Fit Y by X Platform......Page 198
Examine the Plot......Page 199
Display and Compare the Means......Page 200
Inside the Student’s t-Test......Page 201
Equal or Unequal Variances?......Page 202
One-Sided Version of the Test......Page 204
Analysis of Variance and the All-Purpose F-Test......Page 205
How Sensitive Is the Test? How Many More Observations Are Needed?......Page 207
When the Difference Is Significant......Page 209
Normality and Normal Quantile Plots......Page 211
Testing Means for Matched Pairs......Page 213
Thermometer Tests......Page 214
Look at the Data......Page 215
Student’s t-Test......Page 216
The Matched Pairs Platform for a Paired t-Test......Page 217
Optional Topic: An Equivalent Test for Stacked Data......Page 220
Two Extremes of Neglecting the Pairing Situation: A Dramatization......Page 222
Paired Means: The Wilcoxon Signed-Rank Test......Page 228
Independent Means: The Wilcoxon Rank Sum Test......Page 230
Exercises......Page 231
Overview......Page 234
What Is a One-Way Layout?......Page 236
Comparing and Testing Means......Page 238
Means Diamonds: A Graphical Description of Group Means......Page 239
Statistical Tests to Compare Means......Page 240
Means Comparisons for Balanced Data......Page 243
Means Comparisons for Unbalanced Data......Page 244
Adjusting for Multiple Comparisons......Page 249
Are the Variances Equal across the Groups?......Page 252
Testing Means with Unequal Variances......Page 255
Review of Rank-Based Nonparametric Methods......Page 256
The Three Rank Tests in JMP......Page 257
Exercises......Page 259
Overview......Page 262
Least Squares......Page 264
Seeing Least Squares......Page 265
Fitting a Line and Testing the Slope......Page 267
Testing the Slope By Comparing Models......Page 269
The Distribution of the Parameter Estimates......Page 272
Confidence Intervals on the Estimates......Page 273
Exclusion of Rows......Page 275
Polynomial Models......Page 277
Higher-Order Polynomials......Page 278
Distribution of Residuals......Page 279
Transformed Fits......Page 280
Spline Fit......Page 282
Are Graphics Important?......Page 283
Why It’s Called Regression......Page 286
What Happens When X and Y Are Switched?......Page 288
Sometimes It’s the Picture That Fools You......Page 291
High-Order Polynomial Pitfall......Page 292
The Pappus Mystery on the Obliquity of the Ecliptic......Page 293
Exercises......Page 294
Overview......Page 297
Categorical Responses and Count Data: Two Outlooks......Page 299
A Simulated Categorical Response......Page 302
Simulating Some Categorical Response Data......Page 303
Variability in the Estimates......Page 304
Larger Sample Sizes......Page 306
Monte Carlo Simulations for the Estimators......Page 307
Distribution of the Estimates......Page 308
The X2 Pearson Chi-Square Test Statistic......Page 309
The G2 Likelihood-Ratio Chi-Square Test Statistic......Page 310
Likelihood Ratio Tests......Page 311
Univariate Categorical Chi-Square Tests......Page 312
Comparing Univariate Distributions......Page 313
Charting to Compare Results......Page 315
Exercises......Page 317
Overview......Page 318
Testing with G2 and X2 Statistic......Page 320
Looking at Survey Data......Page 321
Car Brand by Marital Status......Page 325
Car Brand by Size of Vehicle......Page 326
Two-Way Tables: Entering Count Data......Page 327
Expected Values under Independence......Page 328
Testing for Independence......Page 329
If You Have a Perfect Fit......Page 331
Special Topic: Correspondence Analysis— Looking at Data with Many Levels......Page 333
Fitting a Logistic Model......Page 336
Degrees of Fit......Page 340
A Discriminant Alternative......Page 341
Inverse Prediction......Page 342
Polytomous (Multinomial) Responses: More Than Two Levels......Page 345
Ordinal Responses: Cumulative Ordinal Logistic Regression......Page 346
Surprise: Simpson’s Paradox: Aggregate Data versus Grouped Data......Page 349
Generalized Linear Models......Page 352
Exercises......Page 357
Overview......Page 359
Regression Definitions......Page 361
A Multiple Regression Example......Page 362
Residuals and Predicted Values......Page 365
The Whole Model F-Test......Page 368
Whole-Model Leverage Plot......Page 369
Effect Leverage Plots......Page 370
Collinearity......Page 372
Exact Collinearity, Singularity, and Linear Dependency......Page 376
The Longley Data: An Example of Collinearity......Page 378
The Case of the Hidden Leverage Point......Page 380
Mining Data with Stepwise Regression......Page 383
Exercises......Page 387
Overview......Page 390
The General Linear Model......Page 392
Types of Effects in Linear Models......Page 393
Coding Scheme to Fit a One-Way anova as a Linear Model......Page 394
Regressor Construction......Page 397
Parameters and Means......Page 398
Analysis of Covariance: Continuous and Categorical Terms in the Same Model......Page 399
The Prediction Equation......Page 402
The Whole-Model Test and Leverage Plot......Page 403
Effect Tests and Leverage Plots......Page 404
Least Squares Means......Page 406
Lack of Fit......Page 407
Separate Slopes: When the Covariate Interacts with a Categorical Effect......Page 409
Two-Way Analysis of Variance and Interactions......Page 413
Optional Topic: Random Effects and Nested Effects......Page 419
Nesting......Page 420
Method 1: Random Effects-Mixed Model......Page 422
Method 2: Reduction to the Experimental Unit......Page 427
Method 3: Correlated Measurements-Multivariate Model......Page 429
Closing Thoughts......Page 431
Exercises......Page 432
Overview......Page 434
Key Concepts......Page 437
JMP DOE......Page 438
The Experiment......Page 439
Enter the Response and Factors......Page 440
Define the Model......Page 442
Perform Experiment and Enter Data......Page 445
Analyze the Model......Page 446
Details of the Design: Confounding Structure......Page 452
How the Custom Designer Works......Page 453
Choices in the Custom Designer......Page 454
An Interaction Model: The Reactor Data......Page 455
Analyzing the Reactor Data......Page 457
Where Do We Go from Here?......Page 463
Main Effects Only (a Review)......Page 465
All Two-Factor Interactions Involving a Single Factor......Page 466
Alias Optimal Designs......Page 468
Response Surface Designs in JMP......Page 469
Analyzing the Odor Response Surface Design......Page 471
Plotting Surface Effects......Page 474
Specifying Response Surface Effects Manually......Page 475
The Custom Designer versus the Response Surface Design Platform......Page 476
Split-Plot Designs......Page 477
Designing the Experiment......Page 478
Analysis of Split-Plot Designs......Page 480
Design Strategies......Page 484
DOE Glossary of Key Terms......Page 485
Exercises......Page 489
Overview......Page 492
Density Estimation......Page 494
Bivariate Density Estimation......Page 495
Mixtures, Modes, and Clusters......Page 497
The Elliptical Contours of the Normal Distribution......Page 498
Simulating Bivariate Correlations......Page 500
Correlations across Many Variables......Page 503
Bivariate Outliers......Page 504
Outliers in Three and More Dimensions......Page 507
Identify Variation with Principal Components Analysis......Page 509
Principal Components for Six Variables......Page 512
How Many Principal Components?......Page 514
Discriminant Analysis......Page 515
Canonical Plot......Page 516
Discriminant Scores......Page 517
Stepwise Discriminant Variable Selection......Page 520
Hierarchical Clustering: How Does It Work?......Page 521
A Real-World Example......Page 524
Some Final Thoughts......Page 527
Exercises......Page 528
Overview......Page 530
Recursive Partitioning (Decision Trees)......Page 532
Growing Trees......Page 534
Exploratory Modeling with Partition......Page 541
Saving Columns and Formulas......Page 543
Neural Nets......Page 544
A Simple Example......Page 545
Saving Columns......Page 548
Profiles in Neural......Page 550
Exercises......Page 554
Overview......Page 558
What Does a Control Chart Look Like......Page 561
Types of Control Charts......Page 562
Variables Charts......Page 563
Control Chart Basics......Page 564
Control Charts for Variables Data......Page 565
The Control Chart Builder Work Space......Page 566
Control Chart Builder Examples......Page 567
Control Charts for Attributes Data......Page 570
Presummarize Charts......Page 573
Uniformly Weighted Moving Average (UWMA) Charts......Page 574
Exponentially Weighted Moving Average (EWMA) Chart......Page 576
What Is Process Capability?......Page 577
Capability for One Process Measurement......Page 580
Capability for Many Process Measurements......Page 582
Capability for Time-Ordered Data......Page 585
Exercises......Page 587
Overview......Page 590
Fitting a Mean......Page 592
Testing a Hypothesis......Page 593
Effect of Sample Size Significance......Page 594
Effect of Error Variance on Significance......Page 595
Experimental Design’s Effect on Significance......Page 596
Simple Regression......Page 597
Leverage......Page 598
Mechanics of Fit for Categorical Responses......Page 599
How Do Pressure Cylinders Behave?......Page 600
Estimating Probabilities......Page 601
One-Way Layout for Categorical Data......Page 602
Logistic Regression......Page 604
Answers......Page 606
Chapter 7, “Univariate Distributions: One Variable, One Sample”......Page 609
Chapter 8, “The Difference Between Two Means”......Page 613
Chapter 9, “Comparing Many Means: One-Way Analysis of Variance”......Page 615
Chapter 10, “Fitting Curves through Points: Regression”......Page 619
Chapter 11, “Categorical Distributions”......Page 622
Chapter 12, “Categorical Models”......Page 623
Chapter 13, “Multiple Regression”......Page 625
Chapter 14, “Fitting Linear Models”......Page 626
Chapter 15, “Design of Experiments”......Page 627
Chapter 16, “Bivariate and Multivariate Relationships”......Page 628
Chapter 18, “Control Charts and Capability”......Page 630
Refs & Data Sources......Page 632
Index......Page 637
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