Giter VIP home page Giter VIP logo

gederajeg / pemahaman_kuantitatif_chisquare Goto Github PK

View Code? Open in Web Editor NEW
0.0 2.0 0.0 253 KB

Source R Markdown file, dataset, and other materials for submitted paper (in Indonesian) on *Linguistik Indonesia*, the journal of the Linguistic Society of Indonesia.

License: Other

TeX 100.00%
chisquare-test indonesian-language indonesian-linguistics form-meaning-pairing metaphors temperature-words temperature-lexical-fields

pemahaman_kuantitatif_chisquare's Introduction

Data and Source R Markdown files with codes for Pemahaman kuantitatif dasar dan penerapannya dalam mengkaji keterkaitan antara bentuk dan makna

Gede Primahadi Wijaya Rajeg ORCID iD icon
I Made Rajeg ORCID iD icon

Creative Commons License
The materials in this repository are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

DOI

The paper (in Indonesian) has just been accepted (with minor revision) for open-access publication in Linguistik Indonesia, the flagship journal for the Linguistic Society of Indonesia (Masyarakat Linguistik Indonesia [MLI]). The post-print version of the paper is available on INA-Rxiv, the Indonesian Preprint Server.

The folder data contains the raw concordance file in plain text format (i.e. panas_raw.txt) used in the paper. The file panas_sample.txt is used as illustrative subset of the raw data.

The paper is written using R Markdown Notebook that mixes prose and R codes together for generating reproducible scientific reports (see Frank & Hartgerink, 2017 for overview). This source R Notebook file is named panas_paper.Rmd and is rendered into an MS Word output using the word_document2() function from the bookdown R package (Xie, 2016).

The repository also includes an RStudio project (i.e. 2018 Oct - PANAS.Rproj). Double-click this file to open an RStudio session associated with data and materials in this repository so that the codes in the source R Markdown Notebook can be executed and run (see Wickham & Grolemund, 2017, Ch. 8 for information on projects-based workflow in RStudio).

devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#>  setting  value                       
#>  version  R version 3.5.1 (2018-07-02)
#>  os       macOS  10.14.3              
#>  system   x86_64, darwin15.6.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_US.UTF-8                 
#>  ctype    en_US.UTF-8                 
#>  tz       Australia/Melbourne         
#>  date     2019-03-06                  
#> 
#> ─ Packages ──────────────────────────────────────────────────────────────
#>  package     * version date       lib source        
#>  assertthat    0.2.0   2017-04-11 [1] CRAN (R 3.4.0)
#>  backports     1.1.2   2017-12-13 [1] CRAN (R 3.5.0)
#>  callr         3.1.1   2018-12-21 [1] CRAN (R 3.5.0)
#>  cli           1.0.1   2018-09-25 [1] CRAN (R 3.5.0)
#>  crayon        1.3.4   2017-09-16 [1] CRAN (R 3.4.1)
#>  desc          1.2.0   2018-05-01 [1] CRAN (R 3.5.0)
#>  devtools      2.0.1   2018-10-26 [1] CRAN (R 3.5.1)
#>  digest        0.6.15  2018-01-28 [1] CRAN (R 3.5.0)
#>  evaluate      0.11    2018-07-17 [1] CRAN (R 3.5.0)
#>  fs            1.2.3   2018-06-08 [1] CRAN (R 3.5.0)
#>  glue          1.3.0   2018-07-17 [1] CRAN (R 3.5.0)
#>  htmltools     0.3.6   2017-04-28 [1] CRAN (R 3.5.0)
#>  knitr         1.20    2018-02-20 [1] CRAN (R 3.5.0)
#>  magrittr      1.5     2014-11-22 [1] CRAN (R 3.4.0)
#>  memoise       1.1.0   2017-04-21 [1] CRAN (R 3.4.0)
#>  pkgbuild      1.0.2   2018-10-16 [1] CRAN (R 3.5.0)
#>  pkgload       1.0.2   2018-10-29 [1] CRAN (R 3.5.0)
#>  prettyunits   1.0.2   2015-07-13 [1] CRAN (R 3.5.0)
#>  processx      3.2.1   2018-12-05 [1] CRAN (R 3.5.0)
#>  ps            1.3.0   2018-12-21 [1] CRAN (R 3.5.0)
#>  R6            2.3.0   2018-10-04 [1] CRAN (R 3.5.0)
#>  Rcpp          1.0.0   2018-11-07 [1] CRAN (R 3.5.0)
#>  remotes       2.0.2   2018-10-30 [1] CRAN (R 3.5.0)
#>  rlang         0.3.1   2019-01-08 [1] CRAN (R 3.5.2)
#>  rmarkdown     1.11    2018-12-08 [1] CRAN (R 3.5.0)
#>  rprojroot     1.3-2   2018-01-03 [1] CRAN (R 3.4.3)
#>  sessioninfo   1.1.1   2018-11-05 [1] CRAN (R 3.5.0)
#>  stringi       1.2.4   2018-07-20 [1] CRAN (R 3.5.0)
#>  stringr       1.3.1   2018-05-10 [1] CRAN (R 3.4.4)
#>  testthat      2.0.1   2018-10-13 [1] CRAN (R 3.5.0)
#>  usethis       1.4.0   2018-08-14 [1] CRAN (R 3.5.0)
#>  withr         2.1.2   2018-03-15 [1] CRAN (R 3.4.4)
#>  yaml          2.2.0   2018-07-25 [1] CRAN (R 3.5.0)
#> 
#> [1] /Users/Primahadi/Rlibs
#> [2] /Library/Frameworks/R.framework/Versions/3.5/Resources/library

References

Frank, M., & Hartgerink, C. (2017, July 31). RMarkdown for writing reproducible scientific papers. Retrieved January 29, 2019, from https://libscie.github.io/rmarkdown-workshop/handout.html

Wickham, H., & Grolemund, G. (2017). R for Data Science. Canada: O’Reilly. Retrieved from http://r4ds.had.co.nz/

Xie, Y. (2016). Bookdown: Authoring Books and Technical Documents with R Markdown. Chapman and Hall/CRC.

pemahaman_kuantitatif_chisquare's People

Contributors

gederajeg avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.