By now it’s no secret that all kinds of organizations are using analytics to take on some of their biggest opportunities. But what about all the opportunities that have the potential to address important human issues that we have overlooked for one reason or another? Those are exactly the types
The latest edition of The American Statistician is dedicated to proposals for living in a post p<.05 world, a world in which a statistical test with a result of “p<.05” is no longer given the importance it has previously been afforded. Decent, honorable researchers once discussed such things only in
Learn how Bayesian optimization works through a simple demo.
Understanding SAS 9.4 architecture is key to tackling the tasks and responsibilities that come with SAS administration, and will help you know where to look to make changes or troubleshoot problems.
As we honor Mental Health Month, there are many calls to reduce suffering. Seems reasonable, right? It’s even in California’s Mental Health Services Act (MHSA), where public systems are called to “reduce subjective suffering.” And as we broadly focus more on outcomes in health, measuring suffering (and hopefully its reduction)
This blog shows how the automatically generated concepts and categories in Visual Text Analytics (VTA) can be refined using LITI and Boolean rules. I will use a data set that contains information on 1527 randomly selected movies: their titles, reviews, MPAA Ratings, Main Genre classifications and Viewer Ratings.
Redefining banking in a financial services market where your biggest competitor may be Amazon or Google, not a traditional bank. Open banking may not have made much of an impression on consumers yet. But it’s a topic that the industry cannot afford to ignore. Tier one UK banks are already
Analytics can bring tremendous value to a business. However, investing in an analytics solution is often easier said than done. The key challenge is demonstrating the value of analytics without first investing in technology and resources. The solution? Take a results-based approach to establish the value of analytics by using
Cold brew coffee is taking over the nation, popping up in coffee shops and stores large and small. This slowed-down, relaxed version of hot coffee yields an incredibly smooth, more palatable and well-rounded tasting coffee that appeals to coffee lovers and non-coffee drinkers alike. It’s no surprise why it’s taking
The eigenvalues of a matrix are not easy to compute. It is remarkable, therefore, that with relatively simple mental arithmetic, you can obtain bounds for the eigenvalues of a matrix of any size. The bounds are provided by using a marvelous mathematical result known as Gershgorin's Disc Theorem. For certain
Marathons seem to be popular these days, therefore I decided to dive into some data and find a way to apply analytics. You might find this interesting if you're a fan of marathons - or if you like seeing the details behind cool graphing techniques! Before we get started, here's
In this blog, I use a Recurrent Neural Network (RNN) to predict whether opinions for a given review will be positive or negative. This prediction is treated as a text classification example. The Sentiment Classification Model is trained using deepRNN algorithms and the resulting model is used to predict if new reviews are positive or negative.
Jim Harris shares three more examples of how data quality improves AI in Part 2 of his series.
If you spend any time working with maps and spatial data, having a fundamental understanding of coordinate systems and map projections becomes necessary. It’s the foundation of how spatial data and maps work. These areas invariably evoke trepidation and some angst, even in the most seasoned map professional. And rightfully
Analytics has an important role to play in supporting the police to keep our communities safe, and I believe the benefits can be far-reaching. In my previous three posts, I discussed the role analytics can play in policing, reviewed the required data and highlighted a police force that is currently
Recently I wrote about how to compute the Kolmogorov D statistic, which is used to determine whether a sample has a particular distribution. One of the beautiful facts about modern computational statistics is that if you can compute a statistic, you can use simulation to estimate the sampling distribution of
As a publishing house inside of SAS, we often hear: “Does anyone want to read books anymore?” Especially technical programmers who are “too busy” to read. About a quarter of American adults (24%) say they haven’t read a book in whole or in part in the past year, whether in
Did you know that you can run Lua code within Base SAS? Learn more about what PROC LUA can do through some examples.
We recently had some severe storms come through North Carolina, which even spawned a tornado in Wake county (the county where I live and work). This got me wondering when and where we've had tornadoes in NC in the past ... and, of course, I had to create a map!
A long time ago, I was working on analytics in a bank, primarily in the area of risk. One project I worked on was about working out which products were profitable to help clean up the product portfolio. The project involved people from both risk and finance. As we worked
In the article Serverless functions and SAS Viya - a good match I discussed using serverless functions to deliver SAS Viya applications. Ignoring all the buzz words, a serverless function boils down to a set of REST APIs. So, if you tried the example you are now a REST API
Customer risk rating models play a crucial role in complying with the Know Your Customer (KYC) and Customer Due Diligence (CDD) requirements, which are designed to assess customer risk and prevent fraud. Today, the most common form of the Customer Risk Rating model is a score-based risk rating model. This
The year was 1987. I was getting ready to enter my freshman year at the University of North Carolina at Chapel Hill – go ahead, do the math. My mom and I received a letter asking us to participate in some research. Would we participate in a mother-daughter bone density
Have you ever run a statistical test to determine whether data are normally distributed? If so, you have probably used Kolmogorov's D statistic. Kolmogorov's D statistic (also called the Kolmogorov-Smirnov statistic) enables you to test whether the empirical distribution of data is different than a reference distribution. The reference distribution
I met many SAS programmers at the 2019 SAS Global Forum who geocode addresses using ArcGIS. Did you know that street address locations and other things can be found using the SAS GEOCODE procedure? PROC GEOCODE gives you coordinates for address, ZIP codes, ZIP+4 codes and cities. You can even
Interested in making business decisions with big data analytics? Our Wiley SAS Business Series book Profit Driven Business Analytics: A Practitioner’s Guide to Transforming Big Data into Added Value by Bart Baesens, Wouter Verbeke, and Cristian Danilo Bravo Roman has just the information you need to learn how to use
In SAS/IML programs, a common task is to write values in a matrix to a SAS data set. For some programs, the values you want to write are in a matrix and you use the CREATE FROM/APPEND FROM syntax to create the data set, as follows: proc iml; X =
May 12th is #NationalLimerickDay! If you saw our Valentine’s Day poem, you know we at SAS Press love creating poems and fun rhymes, so check out our limericks below! So, what’s a limerick? National Limerick Day is observed each year on May 12th and honors the birthday of the famed
You might have seen in the news that US exports of natural gas to Europe are up 300%. And we recently crossed the threshold where we export more natural gas than we import. This seems like a momentous occasion, and worthy of a graph! But first, let me make sure
Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Many believe it’s simply an ovarian condition, but that couldn’t be farther from the truth. Instead, PCOS is a whole-body hormone condition that affects the ovaries. Hormones are the problem, ovaries are the victims.
