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library.bib
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library.bib
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@article{wickham_tidy_2014,
title = {Tidy {Data}},
volume = {59},
copyright = {Copyright (c) 2013 Hadley Wickham},
issn = {1548-7660},
url = {https://www.jstatsoft.org/index.php/jss/article/view/v059i10},
doi = {10.18637/jss.v059.i10},
language = {en},
number = {1},
urldate = {2020-01-31},
journal = {Journal of Statistical Software},
author = {Wickham, Hadley},
month = sep,
year = {2014},
pages = {1--23},
file = {Full Text:/home/jrl/Zotero/storage/HV2FSGYT/Wickham - 2014 - Tidy Data.pdf:application/pdf},
}
@book{navarro_learning_2018,
title = {Learning statistics with jamovi: a tutorial for psychology students and other beginners},
shorttitle = {Learning statistics with jamovi},
url = {https://www.learnstatswithjamovi.com/},
language = {en},
urldate = {2021-03-22},
publisher = {Danielle J. Navarro and David R. Foxcroft},
author = {Navarro, Danielle J and Foxcroft, David R},
year = {2018},
doi = {10.24384/HGC3-7P15},
file = {Navarro and Foxcroft - 2018 - Learning statistics with jamovi a tutorial for ps.pdf:/home/jrl/Zotero/storage/3BQTGV5S/Navarro and Foxcroft - 2018 - Learning statistics with jamovi a tutorial for ps.pdf:application/pdf},
}
@book{hastie_elements_2017,
address = {New York},
edition = {2},
series = {Springer {Series} in {Statistics}},
title = {The {Elements} of {Statistical} {Learning}: {Data} {Mining}, {Inference}, and {Prediction}, {Second} {Edition}},
shorttitle = {The {Elements} of {Statistical} {Learning}},
abstract = {During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression and path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.},
language = {en},
publisher = {Springer-Verlag},
author = {Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome},
year = {2017},
file = {Tibshirani and Friedman - Valerie and Patrick Hastie.pdf:/home/jrl/Zotero/storage/SABSVAKU/Tibshirani and Friedman - Valerie and Patrick Hastie.pdf:application/pdf},
}
@book{crawley_r_2013,
address = {Chichester, West Sussex, UK},
edition = {Second edition},
title = {The {R} book},
isbn = {978-1-118-44896-0 978-1-118-44894-6 978-1-118-44892-2},
url = {https://www.cs.upc.edu/~robert/teaching/estadistica/TheRBook.pdf},
language = {en},
publisher = {Wiley},
author = {Crawley, Michael J.},
year = {2013},
keywords = {Data processing, Mathematical statistics, MATHEMATICS / Probability \& Statistics / General, R (Computer program language)},
file = {Crawley - 2013 - The R book.pdf:/home/jrl/Zotero/storage/TLDQ28AW/Crawley - 2013 - The R book.pdf:application/pdf},
}
@article{dash_flowchart_2016,
title = {Flowchart of statistics for research},
url = {http://rgdoi.net/10.13140/RG.2.2.12014.41283/1},
doi = {10.13140/RG.2.2.12014.41283/1},
language = {en},
urldate = {2021-04-22},
author = {Dash, Ian},
year = {2016},
note = {Publisher: Unpublished},
file = {Dash - 2016 - Flowchart of statistics for research.pdf:/home/jrl/Zotero/storage/NN7YFMSV/Dash - 2016 - Flowchart of statistics for research.pdf:application/pdf},
}
@article{stevens_theory_1946,
title = {On the {Theory} of {Scales} of {Measurement}},
volume = {103},
copyright = {© 1946},
issn = {0036-8075, 1095-9203},
url = {https://science.sciencemag.org/content/103/2684/677},
doi = {10.1126/science.103.2684.677},
language = {en},
number = {2684},
urldate = {2021-04-22},
journal = {Science},
author = {Stevens, S. S.},
month = jun,
year = {1946},
pmid = {17750512},
note = {Publisher: American Association for the Advancement of Science
Section: Articles},
pages = {677--680},
}
@article{bohannon_chocolate_2015,
title = {Chocolate with {High} {Cocoa} {Content} as a {Weight}-{Loss} {Accelerator}},
abstract = {Background: Although the focus of scientific studies on the beneficial properties of chocolate with a high cocoa content has increased in recent years, studies determining its importance for weight regulation, in particular within the context of a controlled dietary measure, have rarely beenconducted.},
language = {en},
number = {2},
author = {Bohannon, Johannes and Koch, Diana and Homm, Peter and Driehaus, Alexander},
year = {2015},
pages = {7},
file = {Bohannon et al. - 2015 - Chocolate with High Cocoa Content as a Weight-Loss.pdf:/home/jrl/Zotero/storage/TYFK2X6Q/Bohannon et al. - 2015 - Chocolate with High Cocoa Content as a Weight-Loss.pdf:application/pdf},
}
@article{duhigg_how_2012,
chapter = {Magazine},
title = {How {Companies} {Learn} {Your} {Secrets}},
issn = {0362-4331},
url = {https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html},
abstract = {Your shopping habits reveal even the most personal information — like when you’re going to have a baby.},
language = {en-US},
urldate = {2021-11-16},
journal = {The New York Times},
author = {Duhigg, Charles},
month = feb,
year = {2012},
keywords = {Statistics, Advertising and Marketing, Books and Literature, Brain, Columbia University, Consumer Behavior, Customer Relations, Data-Mining and Database Marketing, Massachusetts Institute of Technology, PREGNANCY AND OBSTETRICS, Privacy, Procter \& Gamble Company, Psychology and Psychologists, Shopping and Retail, Smells and Odors, Target Corporation, University of Alberta},
}