Course Highlight
Introductory & Advanced Statistics Courses
As SAS Education's statistics curriculum manager, Mike Patetta was closely involved with writing and reviewing the Statistics I and II courses and is well-versed in the field. Mike earned a bachelor's degree in sociology from Notre Dame, a master's degree in geography from the University of North Carolina-Chapel Hill, and completed course work pursuing a doctorate of philosophy in epidemiology.Mike joined SAS after a decade-long stint with North Carolina State's Health Department, where he maintained Medicaid databases and assisted medical examiners and the tuberculosis control branch on statistical projects. As an epidemiologist, he also helped supervise public health program consultants and establish a head and spinal cord surveillance system.
Mike has since been teaching and writing for SAS Education for the past 13 years. So, when we wanted to get more information about the Statistics I and II courses, we knew Mike was the one to see. The following is a brief interview about the courses:
Q: What can students expect to learn in Statistics I?
A: Students will learn basic statistical concepts and how to fit Analysis of Variance models, simple linear regression models, multiple regression models and logistic regression models. Students who are interested in Statistics I and are not programmers should take SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression.View Statistics I schedule and register.
Q: What's covered in Statistics II beyond what students can learn in I?
A: Students will learn advanced modeling techniques such as polynomial regression models, model diagnostics and remedial measures, generalized linear models, n-way Analysis of Variance models, Analysis of Covariance models, and mixed models.View Statistics II schedule and register.
Q: Why take both?
A: If students have limited experience in fitting models in SAS, they should take Statistics I. Students with limited experience in fitting models in SAS who want to become better prepared for the advanced statistical courses offered at SAS should take both. These advanced courses include:- Mixed Models Analyses Using the SAS System
- Multivariate Statistical Methods: Practical Research Applications
- Longitudinal Data Analysis with Discrete and Continuous Responses
- Categorical Data Analysis Using Logistic Regression
- Design of Experiments for Direct Marketing
- Business Forecasting Using SAS: A Point-and-Click Approach
- Determining Power and Sample Size Using SAS/STAT Software
- Fitting Poisson Regression Models Using the GENMOD Procedure
- Or a variety of other courses found within the statistics curriculum.
Q: What are your goals for the stat curriculum this year? What can students expect in terms of courses and scheduling?
A: We're always striving to develop new, compelling content that meets the needs of our customers and addresses their most pressing business issues. One of our key goals right now is to make statistics courses available to SAS users regardless of where they reside. Some of our courses appeal to very targeted audiences. Because it's not cost effective to run public courses with just a couple of students, we've decided to offer many of our statistics courses as Live Web classes. Live Web classes not only aggregate demand, they also save travel costs and reduce time away from the office for our students.Q: In addition to managing, writing and reviewing the curriculum, you also teach from time to time. What's your favorite part of teaching Statistics I and II?
A: When the students tell me how much this material will help them in their jobs, teaching these courses becomes very fulfilling.Quick Links