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Here is a list of the EARL Competition entries we have received so far:
Entry details here
“R is the clear choice for quickly prototyping advanced data manipulation and creating analytics dashboards, essential for a fast, informed response to emerging trends in organised crime”
“The R software ecosystem provides me a cross-platform framework for flexible and extensible quantitative analytics”
“I use R because it is free and has such and extensive & fast-growing array of analytical packages to make it the best product in the statistical software marketplace”
“I use R to perform statistical analysis and predictive model building, in order to increase word’s generosity, make sure every good cause gets funded and help people in need”
“I use R because it’s the Swiss army knife for all of my data DIY”
“I am considering using R to get a distinction in my upcoming Data Science masters!”
“Because R has the most sophisticated and wild package selection”
“I use R daily for financial time series analysis as it is, by far, the most complete and practical tool for such work”
“I am using R because I think it is an extremely elegant, powerful tool for data analysis, modelling and machine learning”
“As a software developer, R allows me to quickly test ideas on a data set with minimal code”
“I am a PhD student in Statistics in Imperial College London. R is a very powerful tool for me. It has many up-to-date packages”
“There R no better tools to manipulate huge amounts of data, use advanced statistical techniques and visualise results, all for free!”
“Because of the huge variety of packages available to do anything and everything”
“Because my awesome supervisor Jenny Bryan introduced me to it on the first day of my graduate degree and since then I’ve learned that analyzing and visualizing data and creating static and interactive reports is very simple”
“R allows me to express ideas quickly, thinking the way I want to, not how a computer needs me to, and whilst I find it intuitive to program in R, free access to an amazing repository of open-source packages, often contributed by leading researchers, means R is always at the cutting edge of data analytics”
“I’m going to use R for developing machine learning algorithms for an event recommendation startup”
“I use R for the depth and breadth of its statistical tools”
“I use R because R is simply the best statistical programming language!”
“To price and differentiate insurance risks for helicopters”
“Because It allows me to code quickly and test several ML algorithm without having to implement them myself”
“With its vast library of packages covering cutting-edge statistical algorithms, a huge community which through forums beats every commercial helpdesk, and more and more APIs to other modern tools, R simply can’t be beaten when it comes to data analysis and modelling in today’s world where we try to solve problems using an evidence-based approach”
I’m considering using R because I have seen a wide range of packages that allow you to carry out anything from awesome visualisations (such as Nightingale charts , which I personally haven’t seen be made in any other software), to really interesting predictive modelling – all constructed with a user friendly code; what could be more exciting!”
“R, is used in my daily workflow for writing, debugging, controlling, and analysing mathematical models of infectious diseases; no other tool allows me to go from source code to publication ready figures in only one language”
“because it’s flexible, comprehensive, shareable and it does everything other expensive software packages do and so much more!”
“At PwC we are already embedded with numerous clients who face difficulties with their data and gaining value from it, currently we mainly help them look backwards but by utilising the power of R we can provide a view of the future allowing them to make proactive decisions rather than just reactive”
“its easy to C that its as easy as Py to learn (or easier) and is STATA-the-art for data analysis”
“Justifying any COTS package is enough of challenge to my clients, I see R as a licence free alternative for many of the things I’d recommend Matlab or Minitab for”
“To help beat blood cancer”
“I use R for making models/algorithms for retail recommendation systems in my role as a data scientist”
“I use R because it is an all-in-one solution for everything I do every day and I don’ t have surf around my PC or internet tools”
“I use R to uncover human behavioural patterns hidden in the noise of data”
“I use R for the wealth of statistics functions and possibilities, because new packages covering novel techniques get added sooner than in other statistics software and for the attractive graphs”
“R is the clear choice for quickly prototyping advanced data manipulation and creating analytics dashboards, essential for a fast, informed response to emerging trends in organised crime”
“I use R because I value my time, sanity and hairline to use any other application”
“Why I use R: I use R because I learned it so ago it’s many surface oddities have come to seem normal – or at least determinate (kind of like the English language)”
“I use R because it is a sexy open source software which allows me to do any hack, visualisation and stats I could imagine. True story”
“I use R because it has the solution to all my problems and haved my PhD”
“This is because R rooted in statistics and adapt to new changing world which makes it unique tool for computation”
“I use R so the science I do today can be reproduced tomorrow”
“I use R because its the best tool out there for general statistical analysis and data wrangling”
“I use r because it enables me to get the job done and the quality of the software and community behind it”
“As a pharma market researcher, I would love to analyse survey data directly, without having to rely on crosstabs created by third party data agencies, and built sound data analysis skills!”
“I use R because I am very excited by the HUGE community that is constantly writing tutorials, sharing knowledge and creating packages to make data manipulation and analysis easier”
“Because R is the only interpreted language with so many statistical packages and can be easily connected to my own C/C++ code”
“I use R because it’s fun!”
“R is a free and fast evolving language with a large community and a broad spectrum of applications. This enables me to draw on the community knowledge to quickly learn and implement any techniques (including both the mainstream statistical analysis and the more obscure tools developed in some university lab or by an oddball genius working from a coffee shop). I can find everything I need to deploy end to end projects from sourcing the data and using predictive analytics to producing data tools and interactive visualisations”
“I am doing Web scraping project in R.”
“I use R because it’s versatile, portable, powerful and extendable (and it’s fantastic that it’s free as well)”
“Because it is fun, easy and powerful”
“I use R for its Graphical capability and ease of which I can write my own code”
“I use R because Hadley packages are just too cool to quit using them”
“Because I’m reaching some limitation in data visualisation in Excel, especially working on huge data sets”
“I use R because the syntax is more natural to me than other languages, has a ever expanding ream of packages, a great user community, its open source and a powerful spatial analysis tool”
“Because it has thousands of awesome packages and is used by a very active community of statisticians and data scientists”
“To produce data processing scripts and data visualisations of viewing behaviour for a major TV broadcaster”
“I use R to embrace the truth with simplicity”
“R theRe any otheR alteRnatives , poweRful yet FRee ?”
“I’ve found R Shiny to be unparalleled for efficiently creating analytic web applications”
“Because it’s betteR than Excel”
“It is very well suited to mathematical programming problems, making coding faster and also easier”
“Because R can; Revolutionize the way you do data science, Reshape your workflow, Reproduce your reports, Read your data, Realize your goals and much much more just with a single letter…”
“I am having a blast looking into complex data and trying to make sense of what others see as plain numbers without sense or meaning”
“To model catastrophe loss risk for insurance companies”
“I turn two-byte integers into biologically-relevant parameters”
“I use R because it allows me to use complex simulation models using differential equations as well as applying Markov Chain Monte Carlo Simulation-Techniques to them, blending different worlds”
“I use R to bring data to life!”
“I use R because most statistical methods are implemented and freely available there in a more or less consistent interface (formula or y and X), typically with little lag time once researchers develop or publish their methods, allowing me to test and apply new methods as soon as I discover them, and be proficient fairly fast due to the low learning curve (fit function, get elements from within object, use generic functions such as predict, etc)”
“R is my first opening software for working for it is clear coded and powerful”
“I use R, because my boss at work and my professor at university allow me to use it even more, when they see my increasing skills in it, which allows me to do my hobby and see a lot of interesting fields, applications and data mining techniques at the same time”
“R, an answer for every analytical issue”
“Starting from initial steps of data gathering process, data manipulation and analysis, and following visualization and presentation abilities, R is, essentially, a complete, cross-platform, and open source ecosystem for current and future data scientist, statistician, and analyst.”
“I use R because I can collect, clean and communicate data in a single document”
“I use R because it’s allows me to go the extra mile in data cleaning and modeling contracts without costing me time”
“Because R is the Lingua Franca of a Marketing & Data Scientist (in a market research business)”
“Languages (human and computer) influence the way I think, and R helps me reach better conclusions, more reliably, in a shorter time”
“Because it just works”
“R is the best, free, open source, state-of-the-art, elegant, efficient programming language to perform my open and reproducible day-to-day data retrieving, -cleaning, -predicting, -visualization tasks!”
“Because if statistics is the grammar of science, R is its pen”
“I use R for its great community and wide array of packages for reproducible data manipulation, analysis, and visualization”
“I have been giving datawarehouse solution for many yrs but with R i could able to give statistical data insights and visualization solutions. R is free, versatile and above all ever expanding (Community, Packages)”
“Through data I can experiment the real world instead of developing strong beliefs in what I want to hear. Reaching the power of Statistics through a decent programming language gives me an impression that this experimenting was never so accessible and powerful”
“Because I wanna be a part of the future”
“I use R because it’s outstanding for data analysis: it can pull data from anywhere, munge it any way I like and then analyse it using the world’s largest collection of analytics packages”
“I use R to make statistics, genomics and bioinformatics analysis of my data easy and fast”
“Because it lets me think cleanly about my data problems”
“Trying to categorise line item description on our platform which worth approximately $5b/year to better suggest product substitutes with machine learning in r, scoop in Python”
“I use R to automate advanced analytics for scalable solutions within my organisation”
“Because I believe it is the quickest way to explore data by visualization and produce high-impact data products such as web-based reports and applications!”
“I use R for predicting sales and email responses as part of the Alteryx analytics package”
“I use R as it is the easiest and quickest software to learn and with lots of support available i can effectively use a wide variety of packages to analyse, present and share my data for my scientific research”
“I want to use R to conduct multilevel Structural Equation Modelling to analyse quantitative daily diary study data for a people analytics project in an organisational setting. Using R will also help us to create a more automated process of producing individual personal reports for employees who take part in the diary studies. I am also intrigued by Shiny and how we could incorporate this into our data collection method and/or a dashboard showing feedback form the diary studies. This is a key part of our new approach to performance management and employee engagement”
“because it helps me express myself and bring my data to life!”
“I use R for access to a wealth of analytics techniques and methods generated through ‘collaborative crowdsourcing’, with contributions from world-leading data scientists and academics”
“R is what we R”
“R is a big deal in my daily Research since I use it to develop, perform, backtest and visualize quantitative trading strategies”
“Because R finds a solution for all my statistical problems – in other words (borrowed from Simon Blomberg): There is no if, only how in R”
“Because, assuming all entries are equally good, it allows me to calculate the probability of winning this competition by using library(rvest)”
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