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Introduction to Statistical Analysis and Outlier Detection Methods

Our friends over at Noah Data have written a research style paper, “Introduction to Statistical Analysis and Outlier Detection Methods,” that discusses how statistical data can generally be classified in terms of number of variables as Univariate, Bivariate or Multivariate. Univariate data has only one variable, Bivariate data has two variables and Multivariate data has more than two variables.

Introduction to Statistical Analysis and Outlier Detection Methods

Our friends over at Noah Data have written a research style paper, Introduction to Statistical Analysis and Outlier Detection Methods, that discusses how statistical data can generally be classified in terms of number of variables as Univariate, Bivariate or Multivariate. Univariate data has only one variable, Bivariate data has two variables and Multivariate data has […]

Statistics and Machine Learning at Scale: New Technologies Apply Machine Learning to Big Data

In a new white paper, based on presentations given over the last few years. Wayne Thompson, Manager of Data Science Technologies at SAS, introduces key machine learning concepts, explains the correlation between statistics and machine learning, and describes SAS solutions that enable machine learning at scale. Download the report to lean more about how new machine learning technologies are being applied to big data.

Book Review: Why – A Guide to Finding and Using Causes

A new book, “ Why: A Guide to Finding and Using Causes ,” by Stevens Institute of Technology assistant professor of computer science Samantha Kleinberg is a necessary addition to any data scientist’s bookshelf as it helps bring focus to the dreaded “correlation does not imply causation” conundrum that affects our understanding of data-centric problems.