Recent & Upcoming Talks

What can we learn about Statistical Inference from a 1960’s experiment with dolphins?

Recent Posts

More Posts

In my work environment, we have users who are not SAS programmers but need to get data from our SAS server. One way of dealing with …

When I was an undergraduate, I learned to distrust the statistical functions in Excel. Back then, we didn’t use software in statistics …

In life, as in math class, it’s important to show your work. In math, when we say, “show your work,” we mean writing down enough of the …

At an event I attended yesterday, the icebreaker was to line up in order of our birthdays. There were about 800 people in attendance. …

When I was an R newbie, I was taught to load packages by using the command library(package). In my Linear Models class, the instructor …

Teaching

Courses taught at Embry-Riddle Worldwide:

Stat 222 Business Statistics

This course is a study of basic descriptive and inferential statistics. Topics include types of data, sampling techniques, measures of central tendency and dispersion, elementary probability, discrete and continuous probability distributions, sampling distributions, hypothesis testing, confidence intervals, and simple linear regression.

Recent Syllabus

Courses taught at
Wake Technical Community College:

BAS-150: Introduction to Analytical Programming

This course introduces SAS for analytics. Topics include utilization of analytical and statistical software packages for data management, data visualization, and exploratory data analysis. Recent Syllabus

BAS-220: Applied Analytical Programming

This course covers applications of SAS for data management and reporting. Topics include data management, data preprocessing, and modeling including linear and logistic regression analysis using programming tools. Upon completion, students should be able to process data and generate reports that support business decision-making.

Recent Syllabus

BAS-230: Applied Predictive Modeling

This course covers advanced applications of predictive models using Python. Topics include the advanced use of classification and regression models in real-world scenarios.