Author:
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 28
Book Description
The Delta Gamma Anchora, Mar. 1885
Author:
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 28
Book Description
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 28
Book Description
The Anchora Delta Gamma, Jan 1885
Author:
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 28
Book Description
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 28
Book Description
The Anchora of Delta Gamma
The Semi-centennial Alumni Record of the University of Illinois
Author: University of Illinois (Urbana-Champaign campus)
Publisher:
ISBN:
Category :
Languages : en
Pages : 1264
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 1264
Book Description
The Glossary of Prosthodontic Terms
Leading Greeks
Author: William Collin Levere
Publisher:
ISBN:
Category : Greek letter societies
Languages : en
Pages : 278
Book Description
Publisher:
ISBN:
Category : Greek letter societies
Languages : en
Pages : 278
Book Description
The Anchora of Delta Gamma
Author:
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 124
Book Description
Publisher: Delta Gamma Fraternity
ISBN:
Category :
Languages : en
Pages : 124
Book Description
The Alumni Record of the University of Illinois
Author: James Herbert Kelley
Publisher:
ISBN:
Category :
Languages : en
Pages : 960
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 960
Book Description
A Detailed Record of Delta Delta Delta, 1888-1907
Author: Amy Olgen Parmelee
Publisher:
ISBN:
Category : Greek letter societies
Languages : en
Pages : 412
Book Description
Publisher:
ISBN:
Category : Greek letter societies
Languages : en
Pages : 412
Book Description
R for Everyone
Author: Jared P. Lander
Publisher: Addison-Wesley Professional
ISBN: 0134546997
Category : Computers
Languages : en
Pages : 1456
Book Description
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.
Publisher: Addison-Wesley Professional
ISBN: 0134546997
Category : Computers
Languages : en
Pages : 1456
Book Description
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.