R Shiny apps Coronavirus tracker COVID-19 outbreak R packages {nCov2019} R code Analyzing COVID-19 outbreak data with R COVID-19 Data Anal

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R Shiny apps Coronavirus tracker COVID-19 outbreak R packages {nCov2019} R code Analyzing COVID-19 outbreak data with R COVID-19 Data Anal
Tim Churches is a Senior Research Fellow at the UNSW Medicine South Western Sydney Clinical School at Liverpool Hospital, and a health data scientist at the Ingham Institute for Applied Medical Research, also located at Liverpool, Sydney. His background is in general medicine, general practice medicine, occupational health, public health practice, particularly population health surveillance, and clinical epidemiology. Introduction As I write this on 4th March, 2020, the world is on the cusp of a global COVID-19 pandemic caused by the SARS-Cov2 virus.
Predictive analytics este: növesztettem egy (véletlen) erdőt. Egész jó lett, a többihez képest.
After several years of successful bootcamps on corpus linguistics as well as statistics for linguists with R, this year offers participants the possibility to
−either take a 30 contact hours corpus linguistics bootcamp, in which they learn how to write R scripts to extract and process data from differently -annotated corpora to generate different types of frequency lists, concordance displays, etc.;
−or take a 30 contact hours statistics for linguistics bootcamp, in which they learn how to use R to perform many different monofactorial significance tests, visualize results, and perform regressions as well as hierarchical cluster analysis;
−or take both in a row to learn, first, how to get data out of corpora and then, second, how to evaluate them statistically.
Taught by Stefan Th. Gries; Organized by Ute Römer & Scott Crossley
Location: Atlanta, GA
Time: August 2013