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Exploratory Data Analysis

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Covers exploratory data summarization techniques that are …

Covers exploratory data summarization techniques that are
applied before modeling to inform development of complex
models. Topics include plotting in R, principles of constructing graphics, and common multivariate techniques used for high dimensional data visualization.

Published in: Data & Analytics
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  • 1. coursera.org Statement of Accomplishment WITH DISTINCTION JULY 08, 2014 DOM FERNANDEZ HAS SUCCESSFULLY COMPLETED THE JOHNS HOPKINS UNIVERSITY'S OFFERING OF Exploratory Data Analysis Covers exploratory data summarization techniques that are applied before modeling to inform development of complex models. Topics include plotting in R, principles of constructing graphics, and common multivariate techniques used for high- dimensional data visualization. ROGER D. PENG, PHD DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH JEFFREY LEEK, PHD DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH BRIAN CAFFO, PHD, MS DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH PLEASE NOTE: THE ONLINE OFFERING OF THIS CLASS DOES NOT REFLECT THE ENTIRE CURRICULUM OFFERED TO STUDENTS ENROLLED AT THE JOHNS HOPKINS UNIVERSITY. THIS STATEMENT DOES NOT AFFIRM THAT THIS STUDENT WAS ENROLLED AS A STUDENT AT THE JOHNS HOPKINS UNIVERSITY IN ANY WAY. IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY GRADE; IT DOES NOT CONFER JOHNS HOPKINS UNIVERSITY CREDIT; IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY DEGREE; AND IT DOES NOT VERIFY THE IDENTITY OF THE STUDENT.

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