R.

Great looking dashboard
Create and Update PowerPoint Reports using R
31 August 2017 | by Tim Bock

In my sordid past, I was a data science consultant. One thing about data science that they don’t teach you at school is that senior managers…

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Complex data visualization example
Layered Data Visualizations Using R, Plotly, and Displayr
30 August 2017 | by Tim Bock

If you have tried to communicate research results and data visualizations using R, there is a good chance you will have come across one of…

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Picture of a sea of blu-ray discs
Analyzing Google Trends Data in R
24 August 2017 | by Jake Hoare

Google Trends shows the changes in the popularity of search terms over a given time (i.e., number of hits over time). It can be used…

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Choice Simulator
How to Create an Online Choice Simulator
22 August 2017 | by Tim Bock

The seven steps to create an online choice simulator are detailed in the post. In addition, an interactive example of a choice simulator is provided…

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correspondence analysis example
Understanding the Math of Correspondence Analysis
08 August 2017 | by Tim Bock

If you’ve ever wanted a deeper understanding of what’s going on behind the scenes of correspondence analysis, then this post is for you. Correspondence analysis…

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singular value decomposition
Singular Value Decomposition (SVD): Tutorial Using Examples in R
02 August 2017 | by Tim Bock

If you have ever looked with any depth at statistical computing for multivariate analysis, there is a good chance you have come across the singular value decomposition…

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preview Show information about the snippet editorYou can click on each element in the preview to jump to the Snippet Editor. SEO title preview: Displayr | Automatically Fitting the Support Vector Machine Cost Parameter
Automatically Fitting the Support Vector Machine Cost Parameter
18 July 2017 | by Jake Hoare

In an earlier post I discussed how to avoid overfitting when using Support Vector Machines. This was achieved using cross validation. In cross validation, prediction accuracy is…

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comparing relative weights and partial least squares
Comparing Partial Least Squares to Johnson’s Relative Weights
19 June 2017 | by Tim Bock

In this post I explore two different methods for computing the relative importance of predictors in regression: Johnson’s Relative Weights and Partial Least Squares (PLS) regression. Both techniques solve a problem with…

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Partial Least Squares can be used find drivers of consumer preference
Using Partial Least Squares to Conduct Relative Importance Analysis in R
19 June 2017 | by Jake Hoare

Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis…

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Using Displayr
Using Partial Least Squares to Conduct Relative Importance Analysis in Displayr
16 June 2017 | by Jake Hoare

Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis…

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statistical significance trick
The Magic Trick that Highlights Interesting Results on Any Table
12 June 2017 | by Tim Bock

This post describes the single biggest time saving technique that I know about for highlighting significant results on a table. The table below, which shows…

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Gradient boosting
Gradient Boosting – The Coolest Kid on The Machine Learning Block
06 June 2017 | by Jake Hoare

Gradient boosting is a technique attracting attention for its prediction speed and accuracy, especially with large and complex data. Don’t just take my word for…

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max-diff-preferences
How to Analyze MaxDiff Data in R
23 May 2017 | by Chris Facer

This post discusses a number of options that are available in R for analyzing data from MaxDiff experiments, using the package flipMaxDiff. For a more detailed…

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correspondence analysis movements
Using Correspondence Analysis to Compare Sub-Groups and Understand Trends
22 May 2017 | by Tim Bock

This post shows how to use correspondence analysis to compare sub-groups. It focuses on one of the most interesting types of sub-groups: data at different points…

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correspondence analysis movements
How to Interpret Correspondence Analysis Plots (It Probably Isn’t the Way You Think)
19 May 2017 | by Tim Bock

Correspondence analysis is a popular data science technique. It takes a large table, and turns it into a seemingly easy-to-read visualization. Unfortunately, it is not quite…

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Max Diff design output
How to Create a MaxDiff Experimental Design in R
17 May 2017 | by Tim Bock

Creating the experimental design for a max-diff experiment is easy in R. This post describes how to create and check a max-diff experimental design. If you are not sure what this is, it would be best to read A beginner’s guide to max-diff first.

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correspondence analysis
Easily Add Images to a Correspondence Analysis Plot in R
17 May 2017 | by Tim Bock

You can take your correspondence analysis plots to the next level by including images. Better still, you don’t need to paste in the images after…

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Scatterplots
Labeled Scatter Plots and Bubble Charts in R
26 April 2017 | by Tim Bock

The rhtmlLabeledScatter R package on GitHub that attempts to solve three challenges with labeled scatter plots: readability with large numbers of labels and bubbles, and the use…

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