Did you know that you can embed one graph inside another by using PROC SGPLOT in SAS? A typical example is shown to the right. The large graph shows kernel density estimates for the distribution of the Cholesterol variable among male and female patients in a heart study. The small
“Change is hard for a lot of people, but it's especially hard in higher education,” says Cali M. Davis, Assistant Professor, Troy University. From changing jobs to changing student attention spans, Davis has experienced a lot of change over her career. She spoke about her experience recently at SAS Explore
I don't often use the SG annotation facility in SAS for adding annotations to statistical graphics, but when I do, I enjoy the convenience of the SG annotation macros. I can never remember the details of the SG annotation commands, but I know that the SG annotation macros will create
When I started my career as an actuarial student in the early 2000s, being successful required a good actuarial exam passing rate and good modeling skills in Visual Basic for Applications (VBA) or using SAS® to code. However, just as SAS never stands still in data analytics, the skillsets required for
Many SAS procedures support a BY statement that enables you to perform an analysis for each unique value of a BY-group variable. The SAS IML language does not support a BY statement, but you can program a loop that iterates over all BY groups. You can emulate BY-group processing by
컴퓨터가 인간보다 잘 하는 몇 가지 분야가 있는데, 그 중 하나가 바로 이미지 인식입니다. 2012년 알렉스넷이 개발된 이후 컴퓨터 비전 분야는 급속도로 성장하여 우리 일상에 자연스럽게 스며들었습니다. 오늘 포스팅에서는 컴퓨터가 이미지를 어떻게 인식할 수 있는지 이론을 중심으로 살펴보도록 하겠습니다. 1. 컴퓨터 비전의 과거 우리가 모니터를 통해 바라보는 이미지의 구조부터 알아보겠습니다.
자금 세탁 방지와 사기 방지 환경의 통합 접근 방안 금융 범죄의 현황과 대응 금융 범죄(Financial Crimes)라 함은 개인적 사용 및 사익을 위해 불법적으로 재산의 소유권을 전환하는 모든 불법 행위를 포함하는 광범위한 용어입니다. 금융 범죄는 다양한 유형의 사기(Fraud), 절도(Theft), 스캠(Scam), 탈세(Tax Evasion), 뇌물 수수(Bribery), 횡령(Embezzlement), 신원 도용(Identity Theft), 위조(Forgery) 등에 의해
Menopause is often looked at as a time of dread, losing femininity and coming face to face with aging. I like to think of it as a time of finding the goddess within. I have personally considered it as a time of self-discovery, feeling comfortable in my own skin, letting
A behind-the-scenes look at women contributing their skills to the battle against child exploitation.
There are many ways to model a set of raw data by using a continuous probability distribution. It can be challenging, however, to choose the distribution that best models the data. Are the data normal? Lognormal? Is there a theoretical reason to prefer one distribution over another? The SAS has
Artículo escrito por Violeta Gállego y Oscar Saavedra. El análisis de los correos recibidos y la priorización de las tareas asociadas a cada uno, es un reto para muchos departamentos que tratan con clientes externos como internos y ven que cada día se acumulan en sus buzones un número de
Does anyone write paper checks anymore? According to researchers at the Federal Reserve Bank of Atlanta (Greene, et al., 2020), the use of paper checks has declined 63% among US consumers since the year 2000. The researchers surveyed more than 3,000 consumers in 2017-2018 and discovered that only 7% of
This summer, women have been making their mark across all industries. From technology to policing, SAS wants to highlight some impactful changes made over the past few months. Click through the articles below to learn about the way women are shaping the future. Intern Spotlight This summer, SAS hired
I have previously written about how to efficiently generate points uniformly at random inside a sphere (often called a ball by mathematicians). The method uses a mathematical fact from multivariate statistics: If X is drawn from the uncorrelated multivariate normal distribution in dimensiond, then S = r*X / ||X|| has
A previous article shows how to use the MODELAVERAGE statement in PROC GLMSELECT in SAS to perform a basic bootstrap analysis of the regression coefficients and fit statistics. A colleague asked whether PROC GLMSELECT can construct bootstrap confidence intervals for the predicted mean in a regression model, as described in
I've written many articles about bootstrapping in SAS, including several about bootstrapping in regression models. Many of the articles use a very general bootstrap method that can bootstrap almost any statistic that SAS can compute. The method uses PROC SURVEYSELECT to generate B bootstrap samples from the data, uses the
실무에서 데이터를 다루다 보면 필연적으로 결측 데이터를 만나게 됩니다. 핑계 없는 무덤이 없다는 속담이 있듯, 데이터가 결측인 이유도 정말 다양합니다. 특별한 경우에만 값이 있는 경우, 서버 장애로 관측되지 않은 경우, 응답자가 응답을 거부하는 경우, 데이터 구조가 바뀌면서 새로운 컬럼이 추가된 경우 등등 너무 다양하죠? 오늘 포스팅에서는 이와 같은 결측치를 처리하는
Artículo escrito por Violeta Gállego y Oscar Saavedra. Los algoritmos de IA combinados con el histórico de las interacciones son el match perfecto para mejorar tus resultados de ventas. Esto es gracias a la mejora en la personalización de las preferencias de los clientes que nos permiten hacer. ¿Qué es?
It has been more than a decade since SAS 9.3 changed the default ODS destination from the old LISTING destination to more modern destinations such as HTML. One of the advantages of modern output destinations is support for Unicode symbols, superscripts, subscripts, and for formatting text by using boldface, italics,
In principle, the best method of mitigating fraud is to set up a strong detection system. A system perceived as unbeatable will mean that potential fraudsters are discouraged from attempting anything and move on to easier targets. The premise of deterrence is that a system that detects fraud and abuse
In ordinary least squares regression, there is an explicit formula for the confidence limit of the predicted mean. That is, for any observed value of the explanatory variables, you can create a 95% confidence interval (CI) for the predicted response. This formula assumes that the model is correctly specified and
SAS Model Manager and the sasctl packages aim to create a seamless ModelOps and MLOps process for Python and R models. Python and R models are not second-class citizens within SAS Model Manager. SAS, Python, and R models can be easily managed using our no-code/low-code interface. This is an interface that can be extended to support a variety of use cases.
La tecnología está cambiando la sociedad a un ritmo cada vez más rápido. Su impacto está presente en todos los ámbitos de la vida y su influencia ha afectado desde la forma de trabajar, hasta la forma de comunicarse, divertirse o informarse. Con una sociedad digitalizada y conectada, la administración
데이터 문해력과 SAS Viya 플랫폼 ‘데이터 문해력과 시민 데이터 사이언티스트(이하 CDS)의 필요 역량’이라는 지난번 블로그 포스팅에 이어, 이번에는 데이터 문해력을 기반으로 CDS를 지원하는 기반 플랫폼 ‘SAS Viya’(쌔스 바이야)의 주요 특징들을 살펴보겠습니다. SAS Viya는 인 메모리, MPP 환경과 Cloud Native 등 최신 기술을 기반으로, 분석의 생애 주기인 데이터 접근, 전 처리,
A SAS programmer wanted to use PROC SGPLOT in SAS to visualize a regression model. The programmer wanted to visualize confidence limits for the predicted mean at certain values of the explanatory variable. This article shows two options for adding confidence limits to a scatter plot. You can use a
The acceptance-rejection method (sometimes called rejection sampling) is a method that enables you to generate a random sample from an arbitrary distribution by using only the probability density function (PDF). This is in contrast to the inverse CDF method, which uses the cumulative distribution function (CDF) to generate a random
Don McMillan - America's top nerdy comedian -- is a featured entertainer at SAS Explore, Sept 11-14 in Las Vegas.
I love the world of science because it’s measurable and can be replicated. I’m also a strong believer in natural remedies because they have been documented for centuries and grow on our beautiful Mother Earth...you just have to know what you’re looking for. While I certainly appreciate pharmaceuticals and believe
SoDA를 이용해 쉽게 배우는 데이터 과학 #2 지난 포스팅에서는 SoDA(SAS Ondemand for Academics)의 장점과 필요성을 중심으로 SoDA가 어떤 제품인지 소개해 드렸습니다. 이번 포스팅에서는 ‘서비스 가입 방법’을 알아보겠습니다. 먼저 SoDA가 서비스 되는 브라우저 환경을 알아보고, 이어서 서비스 가입의 각 단계를 살펴보겠습니다. * 편집자 주 : 이번 글은 SAS코리아 컨설팅 본부 한노아
There are dozens of common probability distributions for a continuous univariate random variable. Familiar examples include the normal, exponential, uniform, gamma, and beta distributions. Where did these distributions come from? Well, some mathematician needed a model for a stochastic process and wrote down the equation for the distribution, typically by
