Back in 2018 we asked our staff what tips they had for how to get to your desk and back in an hour and shared it in our blog. Many of those tips still apply. However, now with many of us still working from home, we may find our desks and
Finding the root (or zero) of a nonlinear function is an important computational task. In the case of a one-variable function, you can use the SOLVE function in PROC FCMP to find roots of nonlinear functions in the DATA step. This article shows how to use the SOLVE function to
Recently, we announced a strategic partnership between SAS and Microsoft that includes deep integration for SAS technologies across all three of Microsoft’s clouds: Azure, Microsoft 365 and Dynamics 365. As migration of data to the cloud continues to increase, SAS is engineering our software to work in the cloud through
Real value comes from data when you can start integrating disparate data sources together.
What is automated prediction? Automated prediction, in less than a minute, runs several analytic models (such as decision trees, gradient boosting, and logistic and linear regression) on a specific variable of your choice. Most of the remaining variables in your dataset are automatically analyzed as factors that might influence your specified variable. They are called underlying factors. SAS then chooses the one model (champion model) that most accurately predicts your target variable. The model prediction and the underlying factors are then displayed. You can adjust the values of the underlying factors to determine how the model prediction changes with each adjustment.
Remember Subconscious Musings? It was the name of the blog Radhika Kulkarni (now retired Vice President of SAS R&D) started in 2012. She wrote about trends that drove innovation and challenges that expanded the boundaries of what we thought was possible. It eventually evolved into what we now know as
Excerpt from Steve Morlidge's new book Present Sense (Matador, 2019). Part 3: Not Storytellers But Reporters This is not the place to explore the role and ethics of performance reporting in detail, but I think there are at least four key duties. The duty of clarity Performance reports should be
Excerpt adapted from Steve Morlidge's new book Present Sense (Matador, 2019). Part 2: Not Storytellers But Reporters News and Evidence If we ever doubted the importance of having a capability to assimilate mountains of detail, synthesize it and present it in an accessible and balanced way, the storm around the
It's no secret that The BFD is a huge fan of Steve Morlidge. Morlidge has contributed work of fundamental importance to our understanding of the practice of business forecasting. His studies of forecast quality exposed the abysmal nature of the practice, including the startling statistic that perhaps 30-50% of real-life
I recently showed how to use simulation to estimate the power of a statistical hypothesis test. The example (a two-sample t test for the difference of means) is a simple SAS/IML module that is very fast. Fast is good because often you want to perform a sequence of simulations over
The International Institute of Forecasters and SAS® announce two $10,000 grants to support research on forecasting. Per the announcement: Forecasting research has seen major changes in the theoretical ideas underpinning forecasting effectiveness over the last 30 years. However, there has been less impact on forecasting practice. We aim to put this right.
Lisa Lucas explains why people, knowledge and tech are vital for contact tracing.
Could you pass a test on coronavirus testing terms? Jim Harris can help.
Bone broth has been around for centuries, it’s the traditional way to make soup or stew. It just seems like a new thing since many of us don’t tend to make soups or broths from scratch anymore. It has become popular due to its supposed healing properties as well.
As he watched me unpack yet another Amazon delivery, my husband decided to do an intervention. Scattered around me on the floor were solar panels, water purification tablets, tarps, hunting knives and enough batteries to power New York City for many weeks. It was 2019 and hurricane season was upon
SAS' Leonid Batkhan reveals how to change lengths for all character variables in a data set and all data sets in a data library to facilitate data migration to Unicode encoding environment.
A previous article about standardizing data in groups shows how to simulate data from two groups. One sample (with n1=20 observations) is simulated from an N(15, 5) distribution whereas a second (with n2=30 observations) is simulated from an N(16, 5) distribution. The sample means of the two groups are close
As we saw in the last installment, The Confidence Man works by making every assertion -- no matter how ridiculous, heinous, or false -- with extreme confidence. By following this practice, with never a waver or inkling of self-doubt, roughly 40% of people will follow along in adoration. If you
Hidden Markov Models Introduction Statistical models of hidden Markov modeling (HMM) have become increasingly popular in the last several years. The models are very rich in mathematical structures and can form the theoretical basis of many real applications. In the classical continuous/discrete Markov process, each state corresponds to an observed
The most fundamental concept that students learning introductory SAS programming must master is how SAS handles data. This might seem like an obvious statement, but it is often overlooked by students in their rush to produce code that works. I often tell my class to step back for a moment
Katherine Taylor explains how and why new data improves risk models.
A common operation in statistical data analysis is to center and scale a numerical variable. This operation is conceptually easy: you subtract the mean of the variable and divide by the variable's standard deviation. Recently, I wanted to perform a slight variation of the usual standardization: Perform a different standardization
Identification of Concepts and Topics based on out-of-the-box rules. It is common practice to develop a business or industry specific taxonomy.
An embedding model is a way to reduce the dimensionality of input data, such as images. Consider this to be a type of data preparation applied to image analysis. When an embedding model is used, input images are converted into low-dimensional vectors that can be more easily used by other computer vision tasks. The key to good embedding is to train the model so that similar images are converted to similar vectors.
In the early days of the COVID-19 pandemic, the issue of tax administration was low on the agenda for most. Beyond the obvious public health concerns, most business and government leaders were focused on how best to keep businesses afloat. But for those in federal, state and local governments responsible
Data collected during the manufacturing process is used to try to identify the cause of discrete problems after the event.
Have you ever seen the "brain teaser" for children that shows a 4 x 4 grid and asks "how many squares of any size are in this grid?" To solve this problem, the reader must recognize that there are sixteen 1 x 1 squares, nine 2 x 2 squares, four 3 x 3 squares, and one 4 x 4 square.
In this guest blogpost, Work/Life welcomes Jamie Pack, College Planning Consultant with Advantage College Planning, to help parents and students sort through the issue of declaring a major…or not…during the college application process. Is there any value in applying to college without a declared major? Yes! In a time where
The iml action was introduced in Viya 3.5. As shown in a previous article, the iml action supports ways to implement the map-reduce paradigm, which is a way to distribute a computation by using multiple threads. The map-reduce paradigm is ideal for “embarrassingly parallel” computations, which are composed of many
I spoke with Antonie Berkel and Dr. Joost Huiskens about a systems analysis project for the design of a clinical decision support system (CDSS) which integrates computer vision to help radiologists monitor the progression of tumors.
