# Dendrograms Explained

There is only one thing worse than a bad visualisation, and that is a good visualisation that you don’t understand.

So if you have ever gone to a conference and the presenter has used a dendrogram assuming you know how to read it, but you didn’t, then this is for you.

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# Curve Fitting

The curve fitting platform allows you to select from a library of model types.

In this post I take a closer look at the different model types that are available to support curve fitting.

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# The Lognormal Distribution

The lognormal distribution is a commonly used distribution for modelling asymmetric data.  It’s just the log of a Normal distribution right?  Well no, it’s actually the other way around.  You take the log of a lognormal distribution to arrive at a normal distribution.  Is it just me, but I always have a bit of a mental block about this, it always feels a bit back to front.

In this post I will explore the relationship between a lognormal distribution and a normal distribution.

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# Capability Indices and Process Shift

In this post I will derive a simple relationship between process shift and the capability indices Cp and Cpk.

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# Visualising the Null Hypothesis

In this post I describe an approach that I use to teach statistics.  The goal is to use JMP to help develop an intuitive understanding of some common concepts: hypothesis testing, p-values and reference distributions.

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# The Range Statistic

Quality control techniques such are control charts and Gage R&R studies sometimes feel as if they are stuck in the pre-computer age.  For example they typically use range as a measure of dispersion since it is far easier to calculate than a standard deviation.(more…)

# Assessing Curvature

Statistics is not about conforming to some strange protocol that we neither agree with nor like.

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# Notation of Model Interaction Terms

Here is a data table that I have created.  It happens to contain data
that is the result of a designed experiment.  I know that, but JMP doesn’t.
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