# Vincent Granville's Blog – May 2019 Archive (18)

### Data Science Central Thursday Digest, May 30

Here is our selection of featured articles and technical resources posted since Monday.

Resources

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Added by Vincent Granville on May 30, 2019 at 10:30am — No Comments

### Simple Trick to Remove Serial Correlation in Regression Models

Here is a simple trick that can solve a lot of problems.

You can not trust a linear or logistic regression performed on data if the error term (residuals) are auto-correlated. There are different approaches to de-correlate the observations, but they usually involve introducing a new matrix to take care of the resulting bias. See for instance here.  …

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Added by Vincent Granville on May 28, 2019 at 9:30am — No Comments

### Gentle Approach to Linear Algebra, with Machine Learning Applications

This simple introduction to matrix theory offers a refreshing perspective on the subject. Using a basic concept that leads to a simple formula for the power of a matrix, we see how it can solve time series, Markov chains, linear regression, data reduction, principal components analysis (PCA) and other machine learning problems. These problems are usually solved with more advanced matrix calculus, including eigenvalues, diagonalization, generalized inverse matrices, and other types of matrix…

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Added by Vincent Granville on May 27, 2019 at 2:00pm — 1 Comment

### Data Science Central Monday Digest, May 27

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…

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Added by Vincent Granville on May 26, 2019 at 8:30am — No Comments

### Data Science Central Thursday Digest, May 23

Here is our selection of featured articles, resources and forum questions posted since Monday:

Technical Resources

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Added by Vincent Granville on May 23, 2019 at 10:30am — No Comments

### 29 Statistical Concepts Explained in Simple English - Part 13

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on May 21, 2019 at 5:30pm — No Comments

### Data Science Central Monday Digest, May 20

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.

Announcements

• Machine…
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Added by Vincent Granville on May 19, 2019 at 3:00pm — No Comments

### A Beautiful Result in Probability Theory

This is another spectacular property of the exponential distribution, and also the first time an explicit formula is obtained for the variance of the range, besides the uniform distribution. It has important consequences, and the result is also useful in applications.

Theorem

The range R(n) associated with n independent random variables with an exponential distribution of parameter l…

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Added by Vincent Granville on May 19, 2019 at 6:30am — 1 Comment

### Data Science Central Thursday Digest, May 16

Here is our selection of featured resources and articles posted since Monday:

Resources

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Added by Vincent Granville on May 16, 2019 at 12:00pm — No Comments

### Free Book: Classification and Regression In a Weekend

By Ajit Jaokar and Dan Howarth. With contributions from Ayse Mutlu.

Exclusively for Data Science Central members, with free access. You can download this book (PDF) here

This tutorial began as a series of weekend workshops created by Ajit Jaokar and Dan Howarth. The idea was to work with a specific (longish) program such that we explore as much of it…

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Added by Vincent Granville on May 16, 2019 at 8:30am — 1 Comment

### 29 Statistical Concepts Explained in Simple English - Part 12

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

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Added by Vincent Granville on May 13, 2019 at 10:00pm — No Comments

### Weekly Digest, May 13

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.

Announcements

• Maximize…
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Added by Vincent Granville on May 12, 2019 at 2:00pm — No Comments

### Data Science Central Thursday Digest, May 9

Here is our selection of featured articles and technical resources posted since Monday.

Resources

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Added by Vincent Granville on May 9, 2019 at 12:30pm — No Comments

### Confidence Intervals Without Pain

We propose a simple model-free solution to compute any confidence interval and to extrapolate these intervals beyond the observations available in your data set. In addition we propose a mechanism  to sharpen the confidence intervals, to reduce their width by an order of magnitude. The methodology works with any estimator (mean, median, variance, quantile, correlation and so on) even when the data set violates the classical requirements necessary to make traditional statistical techniques…

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Added by Vincent Granville on May 6, 2019 at 9:30am — 1 Comment

### Weekly Digest, May 6

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.

Announcements

• Earn a…
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Added by Vincent Granville on May 5, 2019 at 10:00am — No Comments

### Re-sampling: Amazing Results and Applications

This crash course features a new fundamental statistics theorem -- even more important than the central limit theorem -- and a new set of statistical rules and recipes. We discuss concepts related to determining the optimum sample size, the optimum k in k-fold cross-validation, bootstrapping, new re-sampling techniques, simulations, tests of hypotheses, confidence intervals, and statistical inference using a unified, robust, simple approach with easy formulas, efficient…

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Added by Vincent Granville on May 4, 2019 at 9:00am — 7 Comments

### Data Science Central Thursday Digest, May 2

Here is our selection of featured articles and resources posted since Monday:

Resources

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Added by Vincent Granville on May 2, 2019 at 1:00pm — No Comments

### 25 Search Queries Featuring Hundreds of Categorized Articles and Resources

These 25 queries using our own data science search engine, return hundreds of articles and resources, sorted by popularity and recency. This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, …

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Added by Vincent Granville on May 2, 2019 at 5:00am — No Comments

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