In the previous post I illustrated a software advisor that can be used to automatically check the assumptions associated with a oneway analysis of variance. Now I am going to show you how you can write the code from scratch.
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Oneway Advisor
I want to show you an example of some software designed to help you be more productive and consistent in applying statistical tests. It’s designed to work along side a oneway analysis of variance and will automatically assess the assumptions associated with the analysis.
Analysing My Fitness Data
I like watches and the Garmin Forerunner caught my eye. So to justify buying one I’ve had to start running!
Shape Files
I want to take a look at how shape files are organised and how you can create your own custom shapes. I’ll also take a look at an add-in that will help you digitize your shapes. But first I’ll give a short overview of the use of shape files within JMP.
Asserting Your Beliefs
"the programmer should make a number of definite assertions which can be checked individually, and from which the correctness of the whole program follows" - Alan Turin
Performance Profiling
In my last post I illustrated the performance boost generated by using matrix operations to conduct least squares regression calculations. Matrices by their nature require numerical data. So what about handling a categorical predictor variable? To do this it’s necessary to create dummy variables – separate variables for each unique level of the predictor variable.
Regression in Matrix Form
I’m working on some predictive modelling projects and I need to iteratively compute R2 statistics over 100’s of variables. Each time I do the calculations I need to go and have an extended coffee break – and I’m starting to buzz with too much caffeine so I thought I would look to see whether I could make my code more efficient!
Handling Lists of Columns
Note from author: this remains one of the most popular posts on this blog – so I have written an update.
A number of platforms in JMP allow for a variable number of columns. I want to take a look at how to handle this situation using the JMP scripting language.
Column References
A column of a JMP table acts as the primary source of data for most types of analysis within JMP. That is evident by the fact that the first task you perform when you launch a platform is to assign columns to roles:
Escape Sequences
A string variable is created by enclosing a text sequence within double quotes:
str = "this is a string";
If the string needs to contain special characters, including the double quote character itself, the special characters are prefixed with an escape sequence consisting of a backslash (\) following by an exclamation mark (!).