Tag: statistics

Feed: What's New. Author: Erin Gengo, Robert Bloom. As we reimagined data management across all of Tableau, we identified five pillars for the  migration process framework that dovetailed well with our Snowflake selection criteria, and would thereby increase trust and confidence in the data that everyone uses. These pillars are: staffing, governance, authentication, communication, and documentation.  We’ll first discuss staffing, governance, and authentication in this post, highlighting some key lessons learned, unexpected issues with responses, and recommendations to consider when migrating and tackling data sets—large or small, simple or complex. Staffing We don’t want to sugar-coat the complex undertaking of ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. The model-free, data-driven technique discussed here is so basic that it can easily be implemented in Excel, and we actually provide an Excel implementation. It is surprising that this technique does not pre-date standard linear regression, and is rarely if ever used by statisticians and data scientists. It is related to kriging and nearest neighbor interpolation, and apparently first mentioned in 1965 by Harvard scientists working on GIS (geographic information systems). It was referred back then as Shepard's method or inverse distance weighting, and used for multivariate interpolation on ... Read More

Feed: AWS Big Data Blog. The machine learning (ML) lifecycle consists of several key phases: data collection, data preparation, feature engineering, model training, model evaluation, and model deployment. The data preparation and feature engineering phases ensure an ML model is given high-quality data that is relevant to the model’s purpose. Because most raw datasets require multiple cleaning steps (such as addressing missing values and imbalanced data) and numerous data transformations to produce useful features ready for model training, these phases are often considered the most time-consuming in the ML lifecycle. Additionally, producing well-prepared training datasets has typically required extensive knowledge ... Read More

Feed: CIO. Author: . A well-written resume is the foundation of your job hunt; however, resume writing is overwhelming. There’s so much pressure to make your resume stand out, so many formats and styles to choose from. Figuring out how to focus on the most important parts of your career and experiences based on your current job seeking goals is challenging. panom73 / Getty Images Log in or subscribe to Insider Pro to download our resume templates.  Getting your resume just right in order to attract the attention of recruiters, HR pros and hiring managers is in ... Read More

Feed: SAS Blogs. Author: Rick Wicklin. I previously showed how to create a decile calibration plot for a logistic regression model in SAS. A decile calibration plot (or "decile plot," for short) is used in some fields to visualize agreement between the data and a regression model. It can be used to diagnose an incorrectly specified model. In principle, the decile plot can be applied to any regression model that has a continuous regressor. In this article, I show how to create two decile plots for an ordinary least squares regression model. The first overlays ... Read More

Feed: Microsoft Azure Blog. Author: Lucia Stanham. A need for hybrid and multicloud strategies for financial services The financial services industry is a dynamic space that is constantly testing and pushing novel use cases of information technology. Many of its members must balance immense demands—from the pressures to unlock continuous innovation in a landscape with cloud-native entrants, to responding to unexpected surges in demand and extend services to new regions—all while managing risk and combatting financial crime. At the same time, financial regulations are also constantly evolving. In the face of the current pandemic, we have seen our customers accelerate ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Aileen Scott. Data scientist! The most awaited job for candidates who’ve got the affinity for statistics and mathematics. With data growing at an exponential rate, data science now becomes an appealing career path. Data science is super technical, interesting, and tough to get into. However, making an entrance as a data scientist may not be as challenging as you think. First, know that data is being generated in the blink of an eye. To be precise, according to the “2021 Robert Half Technology Salary Guide” data scientist touts to be one ... Read More

Feed: R-bloggers. Author: Econometrics and Free Software. Some weeks ago I tweeted this: GUIs were a mistake — Bruno Rodrigues (@brodriguesco) October 9, 2020 you might think that I tweeted this as an unfunny joke, but it’s not. GUIs were one of the worstthings to happen for statisticians. Clickable interfaces for data analysis is probably one of thegreatest source of mistakes and errors in data processing, very likely costing many millions tocompanies worldwide and is a source of constant embarassment when mistakes happen which cost thereputation, and money, of institutions or people. Remember the infamous Excel mistake by Reinhard and ... Read More

Feed: R-bloggers. Author: Theory meets practice.... Abstract: Slides, R code and video lectures of our 2020 The Mathematics and Statistics of Infectious Disease Outbreaks summer course at Stockholm University are made available to a wider audience. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The markdown+Rknitr source code of this blog is available under a GNU General Public License (GPL v3) license from github. Introduction During the 2020 summer Tom Britton and I gave a course on The Mathematics and Statistics of Infectious Disease Outbreaks at the Department of Mathematics, Stockholm University, Sweden. Pre-requisites for the ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. One hundred fifty-six new packages made it to CRAN in October. Here are my “Top 40” selections in eight categories: Computational Methods, Data, Epidemiology, Mathematics, Machine Learning, Statistics, Utilities, and Visualization. Computational Methods mcmcensemble v 2.0: Provides ensemble samplers for affine-invariant Monte Carlo Markov Chain algorithms which allow a faster convergence for ... Read More