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JMP Tutorial: Confidence Intervals and Prediction Intervals for Regression Response

This is a simple example, with data given, for how to use JMP to get confidence intervals and prediction intervals for a regression model.
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Date Of Record Creation 2005-03-16 13:15:00
Date Last Modified 2013-02-01 16:39:00
Date Of Record Release 2005-03-16 13:15:00
Alternate Title PANDA
Email Address
Date Issued 2000
Resource Type
Typical Learning Time 90 min
Author Name John Mason, Kari Gillenwater, Rena Pugh, Eric Kenefik, Greg Collins, Meri Whitaker, David Volk.
Author Organization Tulane University
General Comments Dead Link.
Technical Requirements Minitab, Excel, Adobe Acrobat Reader
Comments This material is a great resource for doing power and sample size calculations. The combination of visual tools, such as dynamically updating sliders and fully customizable graphing capability, make this item a strong visual aid for teaching power. Unfortunately, because the applets are not intended for instructional use, teachers will have to create materials to accompany these applets for classroom and homework situations.
Content Quality (Concerns) 1. Vocabulary/wording: at least that far away from "mu" in the direction of the arrow 2. Use of what or which 3. p-value is printed over the center of the graph which may suggest the incorrect area (This may be hard to fix due to programming issues). 4. I'd like there to be some comment about how the p-value is used in deciding between the hypotheses. Perhaps even a count of how often the null hypothesis is rejected for a given alpha value.
Content Quality (Strengths) This activity illustrates important content. I really like the blue arrow under the normal curve. It changes direction depending on the alternate hypothesis, and the text points this out to the user. I also like the fact that the user can change the actual value of mu, to see what happens when the null hypothesis is true and what happens when it is false.
Ease of Use (Concerns) When I changed the value of sigma from 1 to 2 while leaving the value of n unchanged, I got a reasonable curve. But if I entered 2 for sigma while changing n to 50, the curve was too skinny.
Ease of Use (Strengths) This is easy to use and has clear instructions. It is limited to those with an internet connection but I don') was explained in the text.
Potential Effectiveness (Concerns) The introduction refers to Section 6.2 of IPS. Since I'm looking at this page as a stand-alone, I do not know what this is referring to.
Potential Effectiveness (Strengths) The shading of under the curve, along with the blue arrow, does a good job of explaining visually how a p-value is calculated. In fact, I will be trying this with my next class, because I've had a difficult time explaining this in the past. The material can easily be integrated into statistics curriculum. It also promotes active engagement.
Content Quality (Rating) 4
Ease of Use (Rating) 4
Potential Effectiveness (Rating) 4
Source Code Available 1
Material Type
Statistical Topic
Application Area
Cost involved with use
Intended User Role
Math Level

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