Tag Archives: data science program

AI on the Edge: What it is, and Data Storage Challenges it Poses

AI on the edge refers to doing the AI processing and equations at the site of the object collecting the data.

“AI on the edge” was a new term for me that I learned from Marc Staimer, founder of Dragon Slayer Consulting, who was interviewed in a podcast. Marc explained how AI on the edge poses a data storage problem, and my blog post proposes a solution!

US Public Health Alphabet Soup Explained: What is the IHS?

The Indian Health Service (IHS) is the federal agency in the United States in charge of reservation health.

“What is the IHS?” is a reasonable question to ask, because there are a few things that are very special about the IHS and its healthcare facilities. At first glance, these special characteristics may seem positive, but they actually have devastating unintended consequences, as I describe in my blog post.

Making Box Plots Different Ways is Easy in R!

There are two main ways to make box plots in R, and this blog post shows you how, and explains the differences.

Making box plots in R affords you many different approaches and features. My blog post will show you easy ways to use both base R and ggplot2 to make box plots as you are proceeding with your data science projects.

Convert CSV to RDS When Using R for Easier Data Handling

If you want to use R for a project and the source CSV is very big, it can improve input/output efficiency to convert the file to an RDS.

Convert CSV to RDS is what you want to do if you are working with big data files in R GUI and want to improve efficiency. Read my blog post for an explanation and video demonstrations of this process!

GPower Case Example Shows How to Calculate and Document Sample Size

This case example shows a use case where we estimated sample size in GPower under different conditions.

GPower case example shows a use-case where we needed to select an outcome measure for our study, then do a power calculation for sample size required under different outcome effect size scenarios. My blog post shows what I did, and how I documented/curated the results.

Variable Names in SAS and R Have Different Restrictions and Rules

You need to come up with names of variables in SAS and in R, but they need to be compatible with both languages if you are running a data warehouse.

Variable names in SAS and R are subject to different “rules and regulations”, and these can be leveraged to your advantage, as I describe in this blog post.

Referring to Variables in Processing Data is Different in SAS Compared to R

When doing data processing, especially extract-transform-load (ETL) into a data warehouse, you might need to refer to the variables in your code, and it's done differently in SAS vs. R.

Referring to variables in processing is different conceptually when thinking about SAS compared to R. I explain the differences in my blog post.

Counting Rows in SAS and R Use Totally Different Strategies

If you are a data scientist working with large datasets, you need to learn the commands to count both columns and rows in the dataset, whether you are using SAS or R.

Counting rows in SAS and R is approached differently, because the two programs process data in different ways. Read my blog post where I describe both ways.

Native Formats in SAS and R for Data Are Different: Here’s How!

Why use particular data formats for different programming languages in statistics? Because the programs can then process the data faster and with more accuracy.

Native formats in SAS and R of data objects have different qualities – and there are reasons behind these differences. Learn about them in this blog post!

Learn to Use SAS ODA (OnDemand for Academics) in my FREE Online Course!

Take this free online course to get up and running with SAS online so you can practice your data analytics

Want to get started with SAS, but don’t want the headache? I make it easy for you! Take my FREE course in getting started with SAS ODA!