Applied Statistics and Data Management Certificate
Gain Sought-after Skills and Knowledge
In this graduate certificate program, students learn important statistical methods (2 courses) and associated statistical programming techniques (2 courses).
Our online program serves a wide audience. We have traditional students that enter directly after their undergraduate studies. However, a large proportion of our online program community have been working for 5+ years and are looking to retool or upscale their careers.
Note that students are not required to have a calculus background to be successful in these 4 courses. However, calculus is required for those who want to continue and obtain our online master’s degree (6 more courses).
The coursework for the certificate requires four courses (12 credits).
Statistical Methods Sequence
Two courses come from an applied methods sequence that focuses on statistical methods and how to apply them in real world settings. This sequence takes learners through a broad spectrum of important statistical concepts and ideas including:
- the basics of understanding data sources, variability of data, and methods to account for that variability
- visualizing and summarizing data using software
- understanding core inference techniques such as confidence intervals and hypothesis testing
- fitting advanced statistical models to the data for the purposes of inference and prediction
These two methods courses are taken from the following sequences:
- ST 511 & ST 512 – Statistical Methods For Researchers I & II
- ST 513 & ST 514 – Statistics for Management and Social Sciences I & II
The course sequences are similar. The main difference is that ST 511 & ST 512 focus more heavily on analysis of designed experiments, whereas ST 513 & ST 514 focus more heavily on the analysis of observational data. However, learners that take ST 511 can readily take ST 514 as their ‘second’ course and similarly those that take ST 513 can take ST 512 as their ‘second’ course.
Two courses come from a selection of statistical programming courses that teach learners statistical programming techniques that are required for managing data in a typical workplace environment. We have courses covering three of the major statistical and data science languages (R, Python, and SAS).
- ST 554 – Big Data Analysis (Python course)
- ST 555 & ST 556 – Statistical Programming I & II (SAS courses)
- ST 558 – Data Science for Statisticians (R course)
Learners can take any two of these courses as part of the certificate. The two SAS courses will prepare you for the highly sought after credentials of Base Programming Specialist and Advanced Programming Using SAS certification.
What is it like to be in our program?
Our learners take one to two courses per semester and finish the certificate in about a year.
We have a diverse and welcoming faculty and staff that want to help our students succeed and reach their potential. To help students from such varied backgrounds achieve their goals, we have a full-time advisor for our online community. This dedicated advisor helps each individual determine the best path for them. This process starts immediately after enrollment. We hold a department orientation session prior to each semester that serves to help students:
- acclimate to our program and start networking
- understand the expectations of graduate school including tips on how to be successful
- learn about all of the fantastic resources that come with attending NC State
- find answers to any other questions
As we use programming in all of our courses and some take the methods courses first, we provide free short courses in SAS, R, and Python to help everyone get up to speed using the languages. Our Basics of R and Basics of SAS course are open and available to anyone.
To build our online community, we use a slack channel and a LinkedIn group to encourage networking and to provide a means for informal student-to-student communication. In addition, we have in-person and online networking events each semester.
The courses for our online program are all taught by our full-time faculty. We do not use adjunct (part-time) professors as many other online programs do. Online students have access to the same professors, lectures, and assessments as our on-campus students. We utilize state-of-the-art tools to facilitate interactions between students, students and the course content, and students and instructors. The online courses are asynchronous – meaning that there are no set times where you must attend class – but are not self-paced. There are deadlines throughout the semester for assignments and exams.