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A Time Series Apologia

I would like to share a new article on some of the methods and pitfalls of time series forecasting: “A Time Series Apologia”. In it I work the seemingly simple problem of forecasting a noisy copy of sin(t). The purpose of the article is to demonstrate using ARIMA methods, and […]

Doing Better than the Average

The standard way to estimate the an expected value of a population from a sample of values v1 … vn is to compute the average (1/n) sumi = 1…nvi. It is well known in statistics that for grouped data, there are other estimators that can have smaller expected square error. […]

The Nature of Overfitting

Introduction I would like to talk about the nature of supervised machine learning and overfitting. One of the cornerstones of our data science intensives is giving the participants the experiences of a data scientist in a safe controlled environment. We hope by working examples they can quickly get to the […]

“Statistics to English Translation”

The core of our “statistics to English translation” series is Nina Zumel’s sequence of articles: “I don’t think that means what you think it means;” Statistics to English Translation, Part 1: Accuracy Measures Statistics to English Translation, Part 2a: ’Significant’ Doesn’t Always Mean ’Important’ Statistics to English Translation, Part 2b: […]

On The Decomposition of Variance

I am conducting another machine learning / AI bootcamp this week. Starting one of these always makes me want to get more statistical commentaries down, just in case I need one. These classes have to move fast, and also move correctly. In this case I want to write about decomposition […]

Unrolling the ROC

In our data science teaching, we present the ROC plot (and the area under the curve of the plot, or AUC) as a useful tool for evaluating score-based classifier models, as well as for comparing multiple such models. The ROC is informative and useful, but it’s also perhaps overly concise […]

Cohen’s D for Experimental Planning

In this note, we discuss the use of Cohen’s D for planning difference-of-mean experiments. Estimating sample size Let’s imagine you are testing a new weight loss program and comparing it so some existing weight loss regimen. You want to run an experiment to determine if the new program is more […]

On accuracy

In our last article on the algebra of classifier measures we encouraged readers to work through Nina Zumel’s original “Statistics to English Translation” series. This series has become slightly harder to find as we have use the original category designation “statistics to English translation” for additional work. To make things […]