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Applied Logistic
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 What are ZValues in Logistic Regression?
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Part 5 — Assessing Uncertainty 
Understanding Logistic Regression Coefficient Output:
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Monthly Archives: February 2012
A Little About Logs
For some reason, which remains mysterious to me, all throughout high school math classes and the first year college math classes (at least in the U.S.), the natural logarithm (the log to the base e) is usually referred to as … Continue reading
What a Multivariate Logistic Regression Data Set Looks Like: An Example
Just to be sure that you have a clear idea of what a data set that is appropriate for logistic regression analysis looks like, I am providing an example in this article. As I indicated in the previous article, a … Continue reading
Posted in Basic
Tagged data mining, logistic regression, multivariate logistic regression
24 Comments
What is (Multivariate) Logistic Regression?
Note: If you want to jump directly to the “punch line” skipping all of my explanation and development (and making me feel unappreciated :() click here. Recall that in regular least squares regression we fit a line to the data. … Continue reading
Why Regular Regression Does NOT Work
It is an error to use regular leastsquares regression when the dependent Yvariable is binary (takes on values of 0 or 1 only). Note: see the previous article When to Use Logistic Regression for a discussion of dichotomous and binary … Continue reading
Posted in Introduction
4 Comments
When to Use Logistic Regression
You should think about using logistic regression when your Y variable takes on only two values. Such a variable is referred to a “binary” or “dichotomous.” “Dichotomous” basically means two categories such as yes/no, defective/nondefective, success/failure, and so on. “Binary” … Continue reading
Posted in Introduction
Tagged binary variable, dependent variable, dichotomous variable, logistic regression, Xvariable, Yvariable
21 Comments