JMP Start Statistics

by Sall, John

• ISBN13: 9780534997496
• ISBN10: 053499749X
• Format: Paperback
• Copyright: 2004-02-23
• Publisher: Duxbury Press

Summary

1. PRELIMINARIES. JMP IN Package Contents and Installation. What You Need to Know. Learning About JMP. Chapter Organization. Typographical Conventions. 2. JMP RIGHT IN. Hello! First Session. Modeling Type. The Personality of JMP. 3. DATA TABLES, REPORTS, AND SCRIPTS. Overview. The Ins and Outs of a JMP Data Table. Creating a New JMP Table. Moving Data Out of JMP. Working with Graphs and Reports. Juggling Data Tables. The Summary Command. Working With Scripts. 4. FORMULA EDITOR ADVENTURES. Overview. The Formula Editor Window. A Quick Example. Formula Editor: Pieces and Parts. The Keypad Functions. The Formula Display Area. Function Browser Definitions. Tips on Building Formulas. Exercises. 5. WHAT ARE STATISTICS? Overview. Ponderings. Preparations. Statistical Terms. 6. SIMULATIONS IN JMP. Overview. Rolling Dice. Probability of Making a Triangle. Confidence Intervals. 7. UNIVARIATE DISTRIBUTIONS: ONE VARIABLE, ONE SAMPLE. Overview. Looking at Distributions. Describing Distributions of Values. Statistical Inference on the Mean. Practical Significance vs. Statistical Significance. Testing for Normality. Special Topic: Practical Difference. Special Topic: Simulating the Central Limit Theorem. Special Topic: Seeing Kernel Addition. Exercises. 8. THE DIFFERENCE BETWEEN TWO MEANS. Overview. Two Independent Groups. Normality and Normal Quantile Plots. Testing Means for Matched Pairs. Special Topic: The Normality Assumption. Two Extremes of Neglecting the Pairing Situation: A Dramatization. A Nonparametric Approach. Exercises. 9. COMPARING MANY MEANS: ONE-WAY ANALYSIS OF VARIANCE. Overview. What is a One-Way Layout? Comparing and Testing Means. Means Diamonds: A Graphical Description of Group Means. Statistical Tests to Compare Means. Means Comparisons for Balanced Data. Means Comparisons for Unbalanced Data. Special Topic: Adjusting for Multiple Comparisons. Are the Variances Equal Across the Groups? Special Topic: Power. Nonparametric Methods. Exercises. 10. FITTING CURVES THROUGH POINTS: REGRESSION. Overview. Regression. Polynomial Models. Transformed Fits. Special Topic: Why Graphics are Important. Special Topic: Why It''s Called Regression. What Happens When x and y are Switched? Curiosities. Exercises. 11. CATEGORICAL DISTRIBUTIONS. Overview. Categorical Situations. Categorical Responses and Count Data: Two Outlooks. A Simulated Categorical Response. The X2 Pearson Chi-Square Test Statistic. The G2 Likelihood Ratio Chi-Square Test Statistic. Univariate Categorical Chi-Square Tests. Exercises. 12. CATEGORICAL MODELS. Overview. Fitting Categorical Responses to Categorical Factors: Contingency Tables. Two-Way Tables: Entering Count Data. If You Have a Perfect Fit. Special Topic: Correspondence AnalysisLooking at Data with Many Level. Continuous Factors with Categorical Responses: Logistic Regression. Special Topics. Surprise: Simpson''s Paradox: Aggregate Data versus Grouped Data. Exercises. 13. MULTIPLE REGRESSION. Overview. Parts of a Regression Model. A Multiple Regression Example. Collinearity. The Longley Data: An Example of Collinearity. The Case of the Hidden Leverage Point. Mining Data with Stepwise Regression. Exercises. 14. FITTING LINEAR MODELS. Overview. The General Linear Model. Two-Way Analysis of Variance and Interactions. Optional Topic: Random Effects and Nested Effects. Exercises. 15. BIVARIATE AND MULTIVARIATE RELATIONSHIPS. Overview. Bivariate Distributions. Density Estimation. Correlations and the Bivariate Normal. Three and More Dimensions. Summary. Exercises. 16. DESIGN OF EXPERIMENTS. Overview. Introduction. JMP DOE. Screening Design Types. Screening for Main Effects. Screening for Interactions: The Reactor Data. Response Surface Designs. A Box-Behnken Design Example. Design Issues. The JMP Custom Designer. Modify a Design Interactively. The Prediction Variance Profiler. Routine Screening Using Custom Designs. Special Topic: How the Custom Designer Works. 17. EXPLORATORY MODELING. Overview. The Partition Platfo

Table of Contents

Preliminaries	p. xv
JMP IN Package Contents and Installation	p. xv
What You Need to Know	p. xvi
...about your computer	p. xvi
...about statistics	p. xvi
Learning About JMP	p. xvi
...on your own with JMP Help	p. xvi
...hands-on examples	p. xvii
...reading about JMP	p. xvii
Chapter Organization	p. xvii
Typographical Conventions	p. xix
Preface	p. xxi
The Software	p. xxi
JMP Start Statistics, Second Edition	p. xxiii
SAS Institute	p. xxiii
This Book	p. xxiii
Jump Right In	p. 1
Hello!	p. 1
First Session	p. 2
Open a JMP Data Table	p. 3
Launch an Analysis Platform	p. 4
Interact with the Surface of the Platform	p. 5
Special Tools	p. 7
Modeling Type	p. 8
Analyze and Graph	p. 9
The Analyze Menu	p. 10
The Graph Menu	p. 11
Navigating Platforms and Building Context	p. 11
Contexts for a Histogram	p. 11
Contexts for the t Test	p. 12
Contexts for a Scatterplot	p. 12
Contexts for Nonparametric Statistics	p. 13
The Personality of JMP	p. 13
JMP Data Tables	p. 15
Overview	p. 15
The Ins and Outs of a JMP Data Table	p. 16
Selecting and Deselecting Rows and Columns	p. 16
Mousing Around a Spreadsheet: Cursor Forms	p. 17
Creating a New JMP Table	p. 19
Define Rows and Columns	p. 19
Enter Data	p. 21
The New Column Command	p. 22
Plot the Data	p. 23
Importing Data	p. 25
Importing Text Files	p. 26
Importing Microsoft Excel Files	p. 27
Copy, Paste, and Drag Data	p. 28
Moving Data in and out of JMP	p. 29
Working with Graphs and Reports	p. 31
Copy and Paste	p. 31
Drag Report Elements	p. 32
Context Menu Commands	p. 32
Juggling Data Tables	p. 33
Data Management	p. 33
Give New Shape to a Table: Stack Columns	p. 35
The Summary Command	p. 37
Create a Table of Summary Statistics	p. 37
Formula Editor Adventures	p. 41
Overview	p. 41
The Formula Editor Window	p. 42
A Quick Example	p. 43
Formula Editor: Pieces and Parts	p. 45
Terminology	p. 45
The Formula Editor Control Panel	p. 46
The Keypad Functions	p. 49
The Formula Display Area	p. 50
Function Browser Definitions	p. 50
Row Function Examples	p. 52
Conditional Expressions and Comparison Operators	p. 55
Summarize Down Columns or Across Rows	p. 58
Random Number Functions	p. 62
Tips on Building Formulas	p. 67
Examining Expression Values	p. 67
Cutting, Dragging, and Pasting Formulas	p. 67
Selecting Expressions	p. 68
Tips on Editing a Formula	p. 68
Exercises	p. 69
What Are Statistics?	p. 73
Overview	p. 73
Ponderings	p. 74
The Business of Statistics	p. 74
Two Sides of Statistics	p. 75
The Faces of Statistics	p. 76
Don't Panic	p. 77
Preparations	p. 78
Three Levels of Uncertainty	p. 78
Probability and Randomness	p. 79
Assumptions	p. 80
Data Mining?	p. 81
Statistical Terms	p. 82
Univariate Distributions: One Variable, One Sample	p. 87
Overview	p. 87
Looking at Distributions	p. 88
Review: Probability Distributions	p. 90
True Distribution Function or Real-World Sample Distribution	p. 91
The Normal Distribution	p. 92
Describing Distributions of Values	p. 94
Generating Random Data	p. 94
Histograms	p. 95
Outlier and Quantile Box Plots: Optional	p. 97
Normal Quantile Plots: Optional	p. 98
Stem-and-Leaf Plot: Optional	p. 101
Mean and Standard Deviation	p. 102
Median and Other Quantiles	p. 103
Mean versus Median	p. 104
Higher Moments: Skewness and Kurtosis	p. 104
Extremes, Tail Detail	p. 105
Statistical Inference on the Mean	p. 105
Standard Error of the Mean	p. 106
Confidence Intervals for the Mean	p. 106
Testing Hypotheses: Terminology	p. 109
The Normal z Test for the Mean	p. 110
Case Study: The Earth's Ecliptic	p. 111
Student's t Test	p. 113
Comparing the Normal and Student's t Distributions	p. 114
Testing the Mean	p. 115
The P Value Animation	p. 116
Power of the t test	p. 118
Curiosity: A Significant Difference?	p. 120
Testing for Normality	p. 122
Special Topic: Practical Difference	p. 125
Special Topic: Simulating the Central Limit Theorem	p. 126
Exercises	p. 128
The Difference Between Two Means	p. 131
Overview	p. 131
Two Independent Groups	p. 132
When the Difference Isn't Significant...	p. 132
Check the Data	p. 132
Launch the Fit Y by X Platform	p. 134
Examine the Plot	p. 135
Display and Compare the Means	p. 135
Inside the Student's t Test	p. 136
One-Sided Version of the Test	p. 137
Analysis of Variance and the All-Purpose F Test	p. 138
How Sensitive Is the Test?
How Many More Observations Are Needed?	p. 140
When the Difference Is Significant	p. 142
Special Topic: Are the Variances Equal Across the Groups?	p. 144
Testing Means with Unequal Variances	p. 147
Special Topic: Normality and Normal Quantile Plots	p. 148
Testing Means for Matched Pairs	p. 150
Thermometer Tests	p. 151
Look at the Data	p. 151
Look at the Distribution of the Difference	p. 152
Student's t Test	p. 153
The Matched Pairs Platform for a Paired t Test	p. 154
Optional Topic: An Equivalent Test for Stacked Data	p. 156
Special Topic: The Normality Assumption	p. 158
Two Extremes of Neglecting the Pairing Situation: A Dramatization	p. 160
A Nonparametric Approach	p. 165
Introduction to Nonparametric Methods	p. 165
Paired Means: The Wilcoxon Signed-Rank Test	p. 166
Independent Means: The Wilcoxon Rank Sum Test	p. 167
Exercises	p. 168
Comparing Many Means: One-Way Analysis of Variance	p. 171
Overview	p. 171
What Is a One-Way Layout?	p. 172
Comparing and Testing Means	p. 173
Means Diamonds: A Graphical Description of Group Means	p. 175
Statistical Tests to Compare Means	p. 175
Means Comparisons for Balanced Data	p. 178
Means Comparisons for Unbalanced Data	p. 179
Special Topic: Adjusting for Multiple Comparisons	p. 183
Special Topic: Power	p. 185
Power in JMP	p. 187
Unequal Variances	p. 189
Nonparametric Methods	p. 190
Review of Rank-Based Nonparametric Methods	p. 190
The Three Rank Tests in JMP	p. 191
Exercises	p. 193
Fitting Curves Through Points: Regression	p. 195
Overview	p. 195
Regression	p. 196
Least Squares	p. 196
Seeing Least Squares	p. 197
Fitting a Line and Testing the Slope	p. 199
Testing the Slope by Comparing Models	p. 201
The Distribution of the Parameter Estimates	p. 203
Confidence Intervals on the Estimates	p. 204
Examine Residuals	p. 206
Exclusion of Rows	p. 207
Time to Clean Up	p. 208
Polynomial Models	p. 209
Look at the Residuals	p. 209
Higher Order Polynomials	p. 210
Distribution of Residuals	p. 210
Transformed Fits	p. 211
Spline Fit	p. 212
Seeing Kernel Addition	p. 213
Special Topic: Why Graphics Are Important	p. 214
Special Topic: Why It's Called Regression What Happens When X and Y Are Switched?	p. 216
Curiosities	p. 220
Sometimes It's the Picture That Fools You	p. 220
High Order Polynomial Pitfall	p. 220
The Pappus Mystery on the Obliquity of the Ecliptic	p. 221
Exercises	p. 222
Categorical Distributions	p. 225
Overview	p. 225
Categorical Situations	p. 226
Categorical Responses and Count Data: Two Outlooks	p. 226
A Simulated Categorical Response	p. 229
Simulating Some Categorical Response Data	p. 230
Variability in the Estimates	p. 231
Larger Sample Sizes	p. 233
Monte Carlo Simulations for the Estimators	p. 233
Distribution of the Estimates	p. 234
The X[superscript 2] Pearson Chi-Square Test Statistic	p. 235
The G[superscript 2] Likelihood Ratio Chi-Square Test Statistic	p. 236
Likelihood Ratio Tests	p. 237
The G[superscript 2] Likelihood Ratio Chi-Square Test	p. 238
Univariate Categorical Chi-Square Tests	p. 239
Comparing Univariate Distributions	p. 239
Charting to Compare Results	p. 241
Exercises	p. 241
Categorical Models	p. 243
Overview	p. 243
Fitting Categorical Responses to Categorical Factors: Contingency Tables	p. 244
Testing with G[superscript 2] and X[superscript 2]	p. 244
Looking at Survey Data	p. 245
Car Brand by Marital Status	p. 248
Car Brand by Size of Vehicle	p. 249
Two-Way Tables: Entering Count Data	p. 250
Expected Values Under Independence	p. 251
Entering Two-Way Data into JMP	p. 251
Testing for Independence	p. 252
If You Have a Perfect Fit	p. 254
Special Topic: Correspondence Analysis: Looking at Data with Many Levels	p. 255
Continuous Factors with Categorical Responses: Logistic Regression	p. 257
Fitting a Logistic Model	p. 258
Degrees of Fit	p. 262
A Discriminant Alternative	p. 262
Special Topics	p. 264
Inverse Prediction	p. 264
Polytomous: More Than Two Response Levels	p. 265
Ordinal Responses: Cumulative Ordinal Logistic Regression	p. 266
Surprise: Simpson's Paradox Aggregate Data versus Grouped Data	p. 270
Exercises	p. 273
Multiple Regression	p. 277
Overview	p. 277
Parts of a Regression Model	p. 278
A Multiple Regression Example	p. 279
Residuals and Predicted Values	p. 281
The Analysis of Variance Table	p. 283
The Whole Model F Test	p. 283
Whole-Model Leverage Plot	p. 284
Details on Effect Tests	p. 285
Effect Leverage Plots	p. 285
Special Topic: Collinearity	p. 287
Exact Collinearity, Singularity, Linear Dependency	p. 290
The Longley Data: An Example of Collinearity	p. 292
Special Topic: The Case of the Hidden Leverage Point	p. 294
Special Topic: Mining Data with Stepwise Regression	p. 296
Exercises	p. 300
Fitting Linear Models	p. 303
Overview	p. 303
The General Linear Model	p. 304
Kinds of Effects in Linear Models	p. 305
Coding Scheme to Fit a One-Way Anova as a Linear Model	p. 306
Regressor Construction	p. 309
Interpretation of Parameters	p. 310
Predictions Are the Means	p. 310
Parameters and Means	p. 310
Analysis of Covariance: Putting Continuous and Classification Terms into the Same Model	p. 311
The Prediction Equation	p. 313
The Whole-Model Test and Leverage Plot	p. 314
Effect Tests and Leverage Plots	p. 315
Least Squares Means	p. 317
Lack of Fit	p. 318
Separate Slopes: When the Covariate Interacts with the Classification Effect	p. 320
Two-Way Analysis of Variance and Interactions	p. 323
Optional Topic: Random Effects and Nested Effects	p. 329
Nesting	p. 330
Repeated Measures	p. 332
Random Effects-Mixed Model	p. 333
Reduction to the Experimental Unit	p. 336
Correlated Measurements-Multivariate Model	p. 337
Varieties of Analysis	p. 340
Summary	p. 340
Exercises	p. 340
Bivariate and Multivariate Relationships	p. 343
Overview	p. 343
Bivariate Distributions	p. 344
Density Estimation	p. 344
Bivariate Density Estimation	p. 345
Mixtures, Modes, and Clusters	p. 347
The Elliptical Contours of the Normal Distribution	p. 348
Correlations and the Bivariate Normal	p. 349
Simulation Exercise	p. 350
Correlations Across Many Variables	p. 352
Bivariate Outliers	p. 354
Three and More Dimensions	p. 355
Principal Components	p. 356
Principal Components for Six Variables	p. 358
Correlation Patterns in Biplots	p. 360
Outliers in Six Dimensions	p. 360
Exercises	p. 363
Design of Experiments	p. 365
Overview	p. 365
Introduction	p. 366
JMP DOE	p. 367
Custom Design	p. 367
Screening Design	p. 368
Response Surface Design	p. 368
Full Factorial Design	p. 368
Taguchi Arrays	p. 369
Mixture Design	p. 369
Augment Design	p. 369
Screening Design Types	p. 370
Two-Level Full Factorial	p. 370
Two-Level Fractional Factorial	p. 370
Resolution Number: The Degree of Confounding	p. 371
Plackett-Burman Designs	p. 371
Screening for Main Effects	p. 372
The Factors	p. 372
Enter and Name the Factors	p. 373
Confounding Structure	p. 375
Make a Design Data Table	p. 376
Perform Experiment and Enter Data	p. 378
Screening for Interactions: The Reactor Data	p. 384
Response Surface Designs	p. 390
A Box-Behnken Design Example	p. 394
Plotting Surface Effects	p. 398
Design Issues	p. 399
Balancing	p. 400
Wide Range	p. 400
Center Points	p. 401
Special Topic: The JMP Custom Designer	p. 402
Modify a Design Interactively	p. 404
The Prediction Variance Profiler	p. 405
Routine Screening Using Custom Designs	p. 409
Special Topic: How the Custom Designer Works	p. 412
Statistical Quality Control	p. 413
Overview	p. 413
Control Charts and Shewhart Charts	p. 414
Variables Charts	p. 415
Attributes Charts	p. 415
The Control Chart Launch Dialog	p. 415
Process Information	p. 416
Chart Type Information	p. 417
Limits Specification Panel	p. 417
Using Known Statistics	p. 418
Types of Control Charts for Variables	p. 418
Types of Control Charts for Attributes	p. 422
Moving Average Charts	p. 423
Tailoring the Horizontal Axis	p. 427
Tests for Special Causes	p. 427
Time Series	p. 431
Overview	p. 431
Introduction	p. 432
Graphing and Fitting by Time	p. 433
Creating Time Columns	p. 433
Graphing by Time	p. 434
Trend and Seasonal Factors	p. 436
Lagging and Autocorrelation	p. 443
Creating Columns with Lagged Values	p. 443
Autocorrelation	p. 444
Autocorrelations with the Time Series Platform	p. 444
Autoregressive Models	p. 445
Special Topic: Moving Average and ARMA Models	p. 448
Special Topic: Simulating Time Series Processes	p. 449
Autoregressive Errors in Regression Models	p. 450
Machines of Fit	p. 451
Overview	p. 451
Springs for Continuous Responses	p. 452
Fitting a Mean	p. 452
Testing a Hypothesis	p. 453
One-Way Layout	p. 454
Effect of Sample Size Significance	p. 454
Effect of Error Variance on Significance	p. 455
Experimental Design's Effect on Significance	p. 455
Simple Regression	p. 456
Leverage	p. 457
Multiple Regression	p. 458
Summary: Significance and Power	p. 458
Machine of Fit for Categorical Responses	p. 458
How Do Pressure Cylinders Behave?	p. 458
Estimating Probabilities	p. 460
One-Way Layout for Categorical Data	p. 461
Logistic Regression	p. 462
JMP vs. JMP IN	p. 465
JMP vs. JMP IN	p. 465
Documentation	p. 465
Technical Support	p. 465
Automation and Data Access	p. 465
Edit Commands	p. 465
Analysis Commands	p. 465
Graph Commands	p. 466
Design of Experiments	p. 466
Data File Reference	p. 467
Main Folder	p. 467
Design of Experiments Folder	p. 474
Nonlinear Examples	p. 475
Quality Control Examples	p. 476
References and Data Sources	p. 479
Index	p. 483
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