Scripting Guide - JMP

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24 Introducing JSL Chapter 1 Samples of JSL Scripts Figure 1.11 Kernel Addition: sigma=15. The Handle is the small black marker at the top of the graph; click and drag this to change the sigma value. Here are a few snapshots after dragging to other sigma values: Figure 1.12 Kernel Addition: Handle Dragged to the Left
Chapter 1 Introducing JSL 25 Samples of JSL Scripts Figure 1.13 Kernel Addition: Handle Dragged to the Right 1 Introducing JSL You can try data of your own as well, but make sure to adjust the coordinates for Handle to suit the range of your data points. Foster, Stine, and Waterman’s illustration use these data, which you might try substituting into the script above: data = [0,3,5,6,7,9]; // Foster, Stine, Waterman's data For more about graph scripting, see “Scripting Graphs,” p. 283. Scripting instructional simulations The previous example, “Scripting graphs,” p. 22, showed JSL’s capability to make interactive graphics— scientific graphics that respond to a user’s clicking and dragging. This capability presents exciting opportunities for educators. For example, many basic statistical methods use t-statistics—tests that rely on the t distribution and the fact that a t distribution with sufficiently many degrees of freedom approximates a normal distribution. The degrees of freedom for a test is defined as the number of subjects in the sample (the sample size, often denoted n), minus the number of parameters in the test. For example, a t-test compares the means of two groups, so a t-test has n – 2 degrees of freedom. Again, the t distribution with sufficiently many degrees of freedom approximates a normal distribution. How many degrees of freedom are sufficient? In other words, how many subjects do you need in your random sample to get reliable results? Many textbooks state the authors’ favorite values for n without much explanation, and many authors’ favorite number seems to be 30. Do you need a sample size of 30 before you can use statistics based on the normal distribution? This script plots the density function for a normal distribution in blue, then draws the density function for a t distribution with just one degree of freedom. There is also a handle that you can click and drag to change the value for df and see how it affects the shape of the t distribution’s density function. df=1;
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Page 5 and 6: iii 4 Programming Functions Script
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Page 9 and 10: vii Definitions . . . . . . . . . .
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Chapter 3 JSL Operators 85 Currency
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Chapter 3 JSL Operators 87 Function
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Chapter 3 JSL Operators 89 Function
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Contents Programming Example. . . .
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Chapter 5 Data Tables Create, open,
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Chapter 5 Data Tables 123 Messages
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Chapter 5 Data Tables 155 Row State
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Chapter 5 Data Tables 171 Calculati
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Contents Scripting analysis platfor
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178 Scripting Platforms Chapter 6 S
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Chapter 7 Display Trees Create and
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Chapter 7 Display Trees 281 Scripti
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Contents Adding Scripts to Graphs .
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286 Scripting Graphs Chapter 8 Addi
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288 Scripting Graphs Chapter 8 Grap
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294 Scripting Graphs Chapter 8 Draw
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308 Scripting Graphs Chapter 8 Inte
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Chapter 9 Three-Dimensional Scenes
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Then use one of these projections:
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Contents Basics . . . . . . . . . .
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Chapter 11 Production Environments
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Contents Functions, Variables, and
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448 JSL Syntax Reference Appendix A
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Appendix B Glossary Terms, concepts
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Appendix B Glossary 647 object An o
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650 Index Beta Binomial Probability
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652 Index Greater or Equal 479 H H
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654 Index Normal Biv Distribution 5
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656 Index Send 545 Sequence 531 Set
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Index JMP Scripting Guide Symbols !
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Index 661 Hierarchical 211 K-Means
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Index 663 Dispatch 235 display 18,
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Index 665 Go To Row 137 Gradient Fu
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