- May 2020
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www.medrxiv.org www.medrxiv.org
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Modi, C., Boehm, V., Ferraro, S., Stein, G., & Seljak, U. (2020). Total COVID-19 Mortality in Italy: Excess Mortality and Age Dependence through Time-Series Analysis. MedRxiv, 2020.04.15.20067074. https://doi.org/10.1101/2020.04.15.20067074
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statmodeling.stat.columbia.edu statmodeling.stat.columbia.edu
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Statistical Modeling, Causal Inference, and Social Science. (2020 April 22). Blog Post: New analysis of excess coronavirus mortality; also a question about poststratification. https://statmodeling.stat.columbia.edu/2020/04/22/analysis-of-excess-coronavirus-mortality-also-a-question-about-poststratification/
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link.aps.org link.aps.org
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Krönke, J., Wunderling, N., Winkelmann, R., Staal, A., Stumpf, B., Tuinenburg, O. A., & Donges, J. F. (2020). Dynamics of tipping cascades on complex networks. Physical Review E, 101(4), 042311. https://doi.org/10.1103/PhysRevE.101.042311
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psyarxiv.com psyarxiv.com
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Olthof, M., Hasselman, F., & Lichtwarck-Aschoff, A. (2020, May 1). Complexity In Psychological Self-Ratings: Implications for research and practice. Retrieved from psyarxiv.com/fbta8
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psyarxiv.com psyarxiv.com
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Horstmann, K. T., Rauthmann, J. F., Sherman, R. A., & Ziegler, M. (2020, April 30). Unveiling an Exclusive Link: Predicting Behavior with Personality, Situation Perception, and Affect in a Pre-Registered Experience Sampling Study. Retrieved from psyarxiv.com/ztw2n
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- Apr 2020
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psyarxiv.com psyarxiv.com
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Edelsbrunner, P. A., & Thurn, C. (2020, April 22). Improving the Utility of Non-Significant Results for Educational Research. https://doi.org/10.31234/osf.io/j93a2
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Wang, T., Chen, X., Zhang, Q., & Jin, X. (2020, April 26). Use of Internet data to track Chinese behavior and interest in COVID-19. https://doi.org/10.31234/osf.io/j6m8q
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Source: Office for National Statistics - United Kingdom
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www.nationalreview.com www.nationalreview.com
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Verbruggen, R. (2020 March 24). Another COVID Cost-Benefit Analysis. National Review. https://www.nationalreview.com/corner/another-covid-cost-benefit-analysis/
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Punn, N. S., Sonbhadra, S. K., & Agarwal, S. (2020). COVID-19 Epidemic Analysis using Machine Learning and Deep Learning Algorithms [Preprint]. Health Informatics. https://doi.org/10.1101/2020.04.08.20057679
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datascience.udd.cl datascience.udd.cl
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Ferres, L., Schifanella, R., Perra, N., Vilella, S., Bravo, L., Paolotti, D., Ruffo, G., & Sacasa, M. (n.d.). Measuring Levels of Activity in a Changing City. 11.
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trello.com trello.com
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Collective Intelligence and COVID-19 | Trello. (n.d.). Retrieved April 20, 2020, from https://trello.com/b/STdgEhvX/collective-intelligence-and-covid-19
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- Feb 2020
- Dec 2019
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www.civilsociety.co.uk www.civilsociety.co.uk
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Foundation finds its grantees 'significantly outperform' similar charities
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- Nov 2019
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rstudio-pubs-static.s3.amazonaws.com rstudio-pubs-static.s3.amazonaws.com
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1. Introduction to eXtensible Time Series, using xts and zoo for time series Introducing xts and
question?
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github.com github.com
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a-little-book-of-r-for-time-series.readthedocs.io a-little-book-of-r-for-time-series.readthedocs.io
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This booklet itells you how to use the R statistical software to carry out some simple analyses that are common in analysing time series data.
what is time series?
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- Sep 2019
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lateraleconomics.com.au lateraleconomics.com.au
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Estimated economic benefit of data linkage
the potential value from linking Census data to administrative data sets is only beginning to be realised and holds immense potential.(In other work for the Population Health Research Network, Lateral Economics concluded that data linkage generated over $16 for every dollar invested).
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- Aug 2019
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labsblog.f-secure.com labsblog.f-secure.com
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Security Issues, Dangers And Implications Of Smart Systems
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- Jul 2019
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www.khanacademy.org www.khanacademy.org
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our sum of squares is 41.187941.187941.1879
Just considering the Y, and not the X. Calculating the residuals from the average/mean Y.
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www.sthda.com www.sthda.com
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it acts as PCA quantitative variables and as MCA for qualitative variables.
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- May 2019
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www.randhome.io www.randhome.io
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Methodology The classic OSINT methodology you will find everywhere is strait-forward: Define requirements: What are you looking for? Retrieve data Analyze the information gathered Pivoting & Reporting: Either define new requirements by pivoting on data just gathered or end the investigation and write the report.
Etienne's blog! Amazing resource for OSINT; particularly focused on technical attacks.
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- Feb 2019
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paleorxiv.org paleorxiv.org
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set; if this is higher, the tree 2can be considered to fit the data less well
To test the fit between data and more than one alternative tree, you can just do a bootstrap analysis, and map the results on a neighbour-net splits graph based on the same data.
Note that the phangorn library includes functions to transfer information between trees/tree samples and trees and networks:<br/> Schliep K, Potts AJ, Morrison DA, Grimm GW. 2017. Intertwining phylogenetic trees and networks. Methods in Ecology and Evolution (DOI:10.1111/2041-210X.12760.)[http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12760/full] – the basic functions and script templates are provided in the associated vignette.
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- Dec 2018
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wendynorris.com wendynorris.com
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Ethnographic findings are not privileged, just particular: another country heard from. To regard them as anything more (or anything less) than that distorts both them and their implications, which are far profounder than mere primitivity, for social theory.
This tension exists in HCI as well.
Interpreted data vs empirical data and how each is systematically analyzed.
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- Sep 2018
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drive.google.com drive.google.com
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Qualitative analysis
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- May 2018
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hypothes.is hypothes.is
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hi there check this link on SAS training and tutorial with the detailed explanation on the Base Training of that along with real time Examples and Projects practices
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hi there please check on the Recent Updated SAS Training and Tutorial Course which can explain about the SAS and its integration with the R as well so please go through the Link:-
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- Apr 2018
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davidbpython.com davidbpython.com
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sqlite> .mode column sqlite> .headers on
At the start of your session,these will format your sqlite3 output so it is clearer, and add columns headers.
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pandas is a Python module used for manipulation and analysis of tabular data.
Introduction to Pandas
Pandas is used to manipulation and analysis of tabular data
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pandas official documentation
pandas reference and tutorials include：full docs, 10minutes to pandas, blog tutorials
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- Dec 2017
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www.nature.com www.nature.com
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Statistical and integrative system-level analysis of DNA methylation data
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- Nov 2017
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rafalab.github.io rafalab.github.ioharvardx1
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HarvardX Biomedical Data Science Open Online Training
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- Sep 2017
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bmcbioinformatics.biomedcentral.com bmcbioinformatics.biomedcentral.com
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The projection score - an evaluation criterion for variable subset selection in PCA visualization
"variable" typically means gene or locus in the context of biological data.
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Local file Local file
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Organizations such as Code for America (CfA) rallied support by positioning civic hacking as a mode of direct partici-pation in improving structures of governance. However, critics objected to the involve-ment of corporations in civic hacking as well as their dubious political alignment and non-grassroots origins. Critical historian Evgeny Morozov (2013a) suggested that “civic hacker” is an apolitical category imposed by ideologies of “scientism” emanating from Silicon Valley. Tom Slee (2012) similarly described the open data movement as co-opted and neoliberalist.
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- Jul 2017
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www.edx.org www.edx.org
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Introduction to R for Data Science
Data analysis course using R
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www.datacamp.com www.datacamp.com
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Learn Data Science Online
Data analysis courses using R and Python
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- May 2017
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fivethirtyeight.com fivethirtyeight.com
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Analysis of a subreddit for Trump supporters, based on comparisons of the users of various subreddits.
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- Dec 2016
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article.sciencepublishinggroup.com article.sciencepublishinggroup.com
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evidence about obtaining higher productivity by using Agile methods
If higher productivity came from including stakeholders in the frequent development releases, running a complementary scrum team on UX analysis should lead to improvement in quality.
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- Sep 2016
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www.sr.ithaka.org www.sr.ithaka.org
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Activities such as time spent on task and discussion board interactions are at the forefront of research.
Really? These aren’t uncontroversial, to say the least. For instance, discussion board interactions often call for careful, mixed-method work with an eye to preventing instructor effect and confirmation bias. “Time on task” is almost a codeword for distinctions between models of learning. Research in cognitive science gives very nuanced value to “time spent on task” while the Malcolm Gladwells of the world usurp some research results. A major insight behind Competency-Based Education is that it can allow for some variance in terms of “time on task”. So it’s kind of surprising that this summary puts those two things to the fore.
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- Apr 2016
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googleguacamole.wordpress.com googleguacamole.wordpress.com
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followed a TAGS Explorer of a conference hashtag
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- Mar 2016
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amstat.tandfonline.com amstat.tandfonline.com
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American Statistical Association statement on p-values
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- Feb 2016
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leanpub.com leanpub.com
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Books on data science and R programming by Roger D. Peng of Johns Hopkins.
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f1000research.com f1000research.com
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Since its start in 1998, Software Carpentry has evolved from a week-long training course at the US national laboratories into a worldwide volunteer effort to improve researchers' computing skills. This paper explains what we have learned along the way, the challenges we now face, and our plans for the future.
http://software-carpentry.org/lessons/<br> Basic programming skills for scientific researchers.<br> SQL, and Python, R, or MATLAB.
http://www.datacarpentry.org/lessons/<br> Managing and analyzing data.
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- Jan 2016
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courses.csail.mit.edu courses.csail.mit.edu
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50 Years of Data Science, David Donoho<br> 2015, 41 pages
This paper reviews some ingredients of the current "Data Science moment", including recent commentary about data science in the popular media, and about how/whether Data Science is really di fferent from Statistics.
The now-contemplated fi eld of Data Science amounts to a superset of the fi elds of statistics and machine learning which adds some technology for 'scaling up' to 'big data'.
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wilkelab.org wilkelab.org
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UT Austin SDS 348, Computational Biology and Bioinformatics. Course materials and links: R, regression modeling, ggplot2, principal component analysis, k-means clustering, logistic regression, Python, Biopython, regular expressions.
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phys.org phys.org
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paradox of unanimity - Unanimous or nearly unanimous agreement doesn't always indicate the correct answer. If agreement is unlikely, it indicates a problem with the system.
Witnesses who only saw a suspect for a moment are not likely to be able to pick them out of a lineup accurately. If several witnesses all pick the same suspect, you should be suspicious that bias is at work. Perhaps these witnesses were cherry-picked, or they were somehow encouraged to choose a particular suspect.
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rpy2.readthedocs.org rpy2.readthedocs.org
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Python interface to the R programming language.<br> Use R functions and packages from Python.<br> https://pypi.python.org/pypi/rpy2
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- Jan 2014
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Once a searchable atlas has been constructed there are fundamentally two approaches that can be used to analyze the data: one visual, the other mathematical.
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