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Many cities have Open Data pages. But once you download the data, what can you do with it? This is my sixth in a series of blog posts where I download public data about Cary, NC, and demonstrate how you might analyze that type of data (for Cary, or any
Technological advancements in connectivity and global positioning systems (GPS) have led to increased data tracking and related business use cases to analyze such movements. Whether analyzing a vehicle, an animal or a population's movements - each use case requires analyzing underlying spatial information. Global challenges such as virus outbreaks, deforestation
Many cities have Open Data pages. But once you download the data, what can you do with it? This is my fifth in a series of blog posts where I download public data about Cary, NC, and demonstrate how you might analyze that type of data (for Cary, or any
Many cities have Open Data pages. But once you download the data, what can you do with it? This is my fourth in a series of blog posts where I download public data about Cary, NC, and demonstrate how you might analyze that type of data (for Cary, or any
In our previous section of the series we discussed the impact of missingness and techniques to address this. In this final section of the series we look at how we can use drag-and-drop tools to accelerate our EDA. As mentioned at the beginning of this series, SAS Viya offers multiple
This article shows how to create a "sliced survival plot" for proportional-hazards models that are created by using PROC PHREG in SAS. Graphing the result of a statistical regression model is a valuable way to communicate the predictions of the model. Many SAS procedures use ODS graphics to produce graphs
Many cities have Open Data pages. But once you download the data, what can you do with it? This is my third in a series of blog posts where I download several datasets from Cary, NC's open data page, and give you a few ideas to get you started on
A previous article discusses the geometry of weighted averages and shows how choosing different weights can lead to different rankings of the subjects. As an example, I showed how college programs might rank applicants by using a weighted average of factors such as test scores. "The best" applicant is determined
Many cities have Open Data pages. But once you download the data, what can you do with it? This is my second blog post where I download several datasets from Cary, NC's open data page, and and give you a few ideas to get you started on your own data
In our last blog we explored the potential impact of missingness in data in terms of its impact on models which require complete case analysis. We took a simple view that data was missing with an equal, independent, probability for any given model input. This week we explore cases where
Many cities have Open Data pages. But once you download this data, what can you do with it? I'm going to download several datasets from Cary, NC's open data page, and try to give you a few ideas to get you started on your own data exploration! And what data
In the previous section of this series we discussed ways of assessing the relationship between variables. This week we change the focus to the shape and sparsity of our dataset. One area of Explanatory Data Analysis which we’ve missed so far is the impact of missingness in data. Having missing
In a previous article, I discussed a beautiful painting called "Phantom’s Shadow, 2018" by the Nigerian-born artist, Odili Donald Odita. I noted that if you overlay a 4 x 4 grid on the painting, then each cell contains a four-bladed pinwheel shape. The cells display rotations and reflections of the pinwheel. The
Some claim that deaths in the US have been increasing, and some claim they have been decreasing. Which do you think is correct? Let's take a look at the data ... The Data Here in the US, the Centers for Disease Control and Prevention is a good/official source of data
"With great power comes great responsibility." I'm not sure exactly where this quote comes from, but I think everyone should keep it in mind when creating graphs and maps! There are many design decisions that can influence how the end user perceives the data in a graph. For example: The
Durante la historia reciente, los gobiernos se han enfrentado a fenómenos económicos que amenazan su estabilidad financiera, creando desempleo y acelerando la urgencia de prestar servicios de apoyo social. Recientemente, una emergencia sanitaria, la de COVID-19, sacudió dicha estabilidad y disparó la demanda de recursos de salud debido a la
How long do dogs live? ... That's a good/tough question. Some live longer than others, but what are the determining factors? Let's throw some data to this problem, and see if we can fetch some answers! But before we get started, how about a random picture to get you into
Following on from my introductory blog series, Data Science in the Wild, we’re going to start delving into how you can scale up and industrialise your Analytics with SAS Viya. In future blogs we will look at how you can augment your R & Python code to leverage SAS Viya
After my recent articles on simulating data by using copulas, many readers commented about the power of copulas. Yes, they are powerful, and the geometry of copulas is beautiful. However, it is important to be aware of the limitations of copulas. This article creates a bizarre example of bivariate data,
We need, in other words, to democratise analytics in the true sense of the word, by making them accessible to everyone.
Who's to say that 'north' should always be at the top of a map? Perhaps in certain situations, you might want 'south' (or some other direction) to be at the top. Perhaps you're one of our crazy Australian customers who looks at the world a little differently. Well, whatever the
I hope you're all doing well, in this year of plagues and locusts! I'm sure I don't even need to mention which plague I'm talking about. But what about the locusts? Are you up on your entomological studies? Follow along, and see if you really know what locusts are... Locusts
Una prioridad para enero del 2022 en el sector asegurador, para aquellas entidades que deban cumplir con IFRS 17, pues estará en marcha el paralelo de esta norma. Aunque si retomamos la frase: “No deje que algo importante se vuelva urgente”, esta tarea debería estar en la agenda del staff
Having earned the Eagle Scout rank in Boy Scouts, I am of course very conservation-minded, and against polluting. I'm also an avid boat paddler and fisherman, and therefore I'm especially concerned about pollution in our rivers, lakes, and oceans. I even volunteered for a week to help survey coral reefs
A previous article showed how to simulate multivariate correlated data by using the Iman-Conover transformation (Iman and Conover, 1982). The transformation preserves the marginal distributions of the original data but permutes the values (columnwise) to induce a new correlation among the variables. When I first read about the Iman-Conover transformation,
Em palestra no Insurance Summit 2021, Agustin Terrile, consultor especializado em seguros do SAS, mostrou um pouco das mudanças do IFRS17 do ponto de vista da estimativa de fluxos de caixa e demonstrou as etapas para um modelo acurado e ágil. Terille começou falando sobre o motor de cálculo e
I've got this buddy, Carter Johnson - he's a little bit crazy, but a lot of fun to follow... He holds/held several different long-distance paddling world records, and was one of the coaches for the group that paddled kayaks from Cuba to the US (see my blog post). A few
You've probably seen a population pyramid, such as this one I showed in a previous blog post. But let's scrutinize population pyramids a bit deeper, with an eye on special features that can make them even more useful! I was inspired to give population trees a second look by this
With the SAS Visual Data Science Decisioning (VDSD) trial, you get the ultimate analytics experience with free access to all SAS Viya analytic capabilities for 14 days. SAS Visual Data Science Decisioning provides the ultimate experience covering the entire analytics lifecycle – from managing data, developing models, and deploying models to take decisions.
In a discussion on a Reddit map group, someone claimed "Maine is the US state closest to Africa." Is that true? Can I use my SAS mapping tools to confirm, or bust, this myth? Follow along, as I dive in! ... The Map in my Head (Wrong!) My gut instincts
