statistics

Packages for Getting Started with Time Series Analysis in R

A. Motivation During the recent RStudio Conference, an attendee asked the panel about the lack of support provided by the tidyverse in relation to time series data. As someone who has spent the majority of their career on time series problems, this was somewhat surprising because R already has a great suite of tools for …

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Statistics Refresher

Let’s face it, a good statistics refresher is always worthwhile. There are times we all forget basic concepts and calculations. Therefore, I put together a document that could act as a statistics refresher and thought that I’d share it with the world. This is part one of a two part document that is still being completed. This refresher …

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Statistical Reading Rainbow

For those of us who received statistical training outside of statistics departments, it often emphasized procedures over principles. This entailed that we learned about various statistical techniques and how to perform analysis in a particular statistical software, but glossed over the mechanisms and mathematical statistics underlying these practices. While that training methodology (hereby referred to …

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Applied Statistical Theory: Quantile Regression

This is part two of the ‘applied statistical theory’ series that will cover the bare essentials of various statistical techniques. As analysts, we need to know enough about what we’re doing to be dangerous and explain approaches to others. It’s not enough to say “I used X because the misclassification rate was low.” Standard linear …

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Basic Forecasting

Forecasting refers to the process of using statistical procedures to predict future values of a time series based on historical trends. For businesses, being able gauge expected outcomes for a given time period is essential for managing marketing, planning, and finances. For example, an advertising agency may want to utilizes sales forecasts to identify which …

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