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The Johnson system (Johnson, 1949) contains a family of four distributions: the normal distribution, the lognormal distribution, the SB distribution, and the SU distribution. Previous articles explain why the Johnson system is useful and show how to use PROC UNIVARIATE in SAS to estimate parameters for the Johnson SB distribution
El coronavirus ha sido un tema importante en las noticias últimamente: es una enfermedad similar a la neumonía que ha cobrado la vida de varias personas. Se cree que comenzó en China y se ha extendido a varios otros países, por lo que debemos estar preparados en caso de que
Alors que certains annonçaient encore récemment la mort du commerce de détail en magasin, prédiction confortée par la croissance explosive d'Amazon, nous avons clairement vu se profiler une seconde vie des magasins en nous promenant dans les couloirs du Javitz Center de New York pendant la NRF 2020. Le commerce
The amount of data collected and analyzed by hospitals and health care organizations across the world was already on the rise, but the global pandemic has sharpened the focus on data even more. With trends changing not daily, but hourly, during the pandemic, health care professionals struggle to monitor larger
Assessing a company from the outside can be tricky business – but it shouldn’t be. That’s why we’re pulling back the curtain on the #saslife. From our values to our vision for the future, we’re giving a transparent look at what it’s really like to work here. At SAS, it’s
You can represent every number as a nearby integer plus a decimal. For example, 1.3 = 1 + 0.3. The integer is called the integer part of x, whereas the decimal is called the fractional part of x (or sometimes the decimal part of x). This representation is not unique.
Starting your data scientist journey? Want to build your own predictive models? SAS' Xavier Bizoux shows you how to use SAS Visual Analytics to identify which model likely to perform the best.
Fraud is a major issue for businesses across all industries, regardless of their size and industry in which they operate. The costs can be enormous (in extreme cases, even fatal) and include far more than the direct costs of any particular type of fraud. Companies must also deal with the
While Brexit has distracted us for the past few years, a far more subtle but important revolution has been happening right under our noses. Artificial intelligence (AI) has become a crucial part of our day-to-day. Self-learning machines are embedded in services or devices used by three-quarters of global consumers. And
The digital world around us is full of data that needs analysing. Maths has become visibly more important.
This blog is a part of a series on the Data Science Pilot Action Set. In this blog, we discuss updates to Visual Data Mining and Machine Learning with the release of Viya 3.5. In the middle of my blog series, SAS released Viya 3.5. Included in Viya 3.5 was the
El sector financiero es de los más avanzados en el uso de las herramientas de analítica, en función del modelo analítico puede evaluarse el riesgo de crédito y cartera, cumplir con las regulaciones gubernamentales, determinar qué productos financieros ofrecer, entre muchas otras aplicaciones. Sin embargo, los bancos enfrentan el reto
Introducing Guest Blogger: Shelly Starling Shelly is a Fitness/Wellness intern at the Recreation and Fitness Center. She is pursuing an Associates degree in Health and Fitness Science at Wake Technical Community College. Her interest in mind/body connection led her to pursue her 200 hour yoga certification in 2017. She enjoys
One of the first and most important steps in analyzing data, whether for descriptive or inferential statistical tasks, is to check for possible errors in your data. In my book, Cody's Data Cleaning Techniques Using SAS, Third Edition, I describe a macro called %Auto_Outliers. This macro allows you to search
A SAS programmer wanted to create a graph that illustrates how Deming regression differs from ordinary least squares regression. The main idea is shown in the panel of graphs below. The first graph shows the geometry of least squares regression when we regress Y onto X. ("Regress Y onto X"