Nearly every statistician has heard the aphorism, "All models are wrong, but some are useful." The quote is attributed to George Box, an early and influential thinker about statistics. Did George Box actually say this quote? Yes, he did. The quote appears on p. 424 of Box and Draper (1987,
Get an overview of how the SAS Strategic Supply Chain Optimization model tackles complex supply chain challenges.
Synthetic data has become a valuable resource in data science and machine learning. Superior quality, reliable synthetic data facilitates analysis and iteration at scale while mitigating privacy concerns associated with real data and can fill gaps where real data is scarce. Note, however, that “good” synthetic data is not defined
What if your cloud analytics environment was smart enough to spin up the exact amount of computing resources required for any specific job? What if you had an AI tool that could determine your computing needs for any given analytics project, scale up to run the job and then scale
After giving a talk about how to create effective statistical graphics in SAS, I was asked a question: "When do you suggest using the graph template language (GTL) to build graphs?" I replied that I turn to the GTL when I cannot create the graph I want by using PROC
Having excellent skills in math is an advantage in a world increasingly driven by technological change. It’s a key to opening doors to high-paying careers and opportunities. Research by the Urban Institute shows that students equipped with advanced math skills earn higher wages throughout their lives. With jobs in data
Integrating AI and machine learning into anti-money laundering (AML) and combating the financing of terrorism (CFT) systems has become imperative for financial institutions (FIs) to safeguard their operations, customers and reputation effectively. Sophisticated financial crimes require advanced solutions to detect and prevent fraud. Money laundering, for example, is a financial
Many popular products from brightly colored candies and cereals to neon pickles to vibrant drinks get their eye-catching appeal from synthetic food dyes. But beneath their dazzling hues lies a complex, controversial web of science, regulation and risk. So, let’s explore the history of synthetic food dyes and uncover potential
Digital twins are revolutionizing manufacturing by providing real-time, virtual representations of physical assets. The ability to create and refine digital replicas using live sensor data is optimizing efficiency, reducing downtime and unlocking new levels of innovation. While many organizations are still operating with “digital shadows” – historical data models that
Navigating the interpretability paradox of autonomous AI: Can we maintain trust and transparency without sacrificing performance? AI has rapidly evolved from simple, rule-based systems into sophisticated autonomous agents capable of making decisions without direct human oversight. These advanced systems, known as "agentic AI," go beyond basic automation to independently sense
At SAS, we believe that prioritizing employee well-being is the right thing to do for our people; it also makes good business sense. We know that life doesn’t stop when we log on or walk into the office, and that’s why we offer unique resources like our onsite Health Care
A common task in statistics is to model data by using a parametric probability distribution, such as the normal, lognormal, beta, or gamma distributions. There are many ways to assess how well the model fits the data, including graphical methods such as a Q-Q plot and formal statistical tests such
Although large language models (LLMs) dominated the spotlight in 2024, SAS' David Weik sheds light on other exciting developments that have largely flown under the radar. He explores what makes transformers so unique.
Imagine a world where data doesn’t just sit in spreadsheets but drives smarter decisions and sparks innovation. Across the globe, companies are tapping into advanced forecasting and analytics to make this a reality. From rethinking forecasting as a global materials science leader to refining processes in the transportation sector, these
Reading McKinsey's article How Banks Can Supercharge Technology Speed and Productivity, released around the same time as SAS' From Data to Decision: Increasing AI Productivity with SAS® Viya®, sparked an epiphany for me. My last job before entering the technology industry was as a product manager at a super-regional bank.
Find out more about the importance and processes involved in model evaluation to become a more productive member of any analytical team
AI has been largely reactive for years: following human commands, assisting with tasks and providing insights based on predefined rules. But 2025 is shaping up to be the year of agentic AI, where AI agents exist to not just respond to human input but act independently. In the movie I, Robot, there's
Every programmer makes errors. Therefore, learning to debug a program is an important part of learning to program. Another skill is learning to decipher cryptic error messages, which can be as hard to interpret as hieroglyphs. One helpful skill is learning to navigate a "traceback" error. A traceback error message
Wouldn’t it be great if we could create a Python environment with only the packages and versions we need? Enter: virtual environments.
UK banks are under growing pressure to manage risks more effectively, whether from economic shifts, technological advances or geopolitical uncertainty. The Bank of England’s Prudential Regulation Authority (PRA) sent a letter to the CEOs of UK deposit holders outlining its supervisory priorities for 2025. The letter sets expectations for stronger
Our eyes are a key sensory organ, allowing us to see and perceive the world around us. But, just like any other organ, they need proper care to stay healthy. In addition to regular eye exams and good hygiene, proper nutrition also plays a crucial role in maintaining vision and
As AI agents gain autonomy, who governs their actions? How do we ensure they align with human values, ethical standards, and legal frameworks? The urgency of governance for AI agents AI is no longer just a tool – it is becoming an actor in decision-making processes. From AI research assistants
Happy Pi Day! Every year on March 14th (written 3/14 in the US), people in the mathematical sciences celebrate "all things pi-related" because 3.14 is the three-decimal approximation to π ≈ 3.14159265358979.... The purpose of this day is to have fun, celebrate the importance of mathematics, and maybe learn a
This article provides a step-by-step guide on manually installing VS Code extensions when access to the online marketplace is restricted, including downloading .vsix files from GitHub and handling dependencies.
AI agents are the tech trend of the moment. It is promising to reshape industries, streamline operations, enhance customer experiences and drive smarter decision-making in ways we couldn’t have imagined just a few years ago. As businesses, leaders, and innovators, it’s vital to understand how these systems actually function, not
Where were you when the global banking crisis of 2008 hit? I was in banking – marketing, to be specific – and I supported our mortgage department. I vividly recall our bank’s chief risk officer repeatedly refusing to enter the adjustable-rate mortgage subprime lending business. Many banks were eating our
AI is reshaping insurance – from streamlining underwriting and fraud detection to fighting climate risk.
In today's digital age, marketing technology (MarTech) plays a crucial role in how businesses engage with their customers. However, the success of truly contextual customer engagement hinges on one fundamental principle: trust. Building and maintaining customer trust is essential for long-term business success, as it fosters loyalty and contributes to
AI and automation – often referred to as hyperautomation – are evolving rapidly with industry experts emphasizing their increasing ability to operate independently and make intelligent decisions. By combining powerful generative AI with business expertise, organizations can accelerate and streamline their processes like never before. I recently sat down with Mayank
The first-order autoregressive (AR(1)) correlation structure is important for applications in time series modeling and for repeated measures analysis. The AR(1) model provides a simple situations where measurements (on the same subject) that are closer in time are correlated more strongly than measurements recorded far apart. The AR(1) model uses
