This course introduces students to techniques of data analysis and statistical inference based on the General Linear Model (GLM). The major topics covered in this class include simple/multiple regression, one- and two-way Analysis of Variance (ANOVA) followed by multiple comparisons, Analysis of Covariance (ANCOVA), and Repeated Measures ANOVA. This course aims to provide a solid conceptual background of these topics, as well as the analytic skills for conducting educational and psychological research in practice. Knowledge of basic algebra and SPSS is required, as is an understanding of the fundamental principles of descriptive statistics and hypothesis testing. Knowledge of calculus is not required. Students will conduct statistical analyses using real datasets.

This course will provide: (1) a conceptually-oriented introduction to regression methods and (2) opportunities to learn related data-analytic techniques.

This course introduces the use of statistical software packages R for acquiring, managing, and preparing datasets that are required to produce reliable and valid statistical inferences. With a special focus on R, the course will cover a broad range of hands-on activities in the data analytic process including data coding, file manipulation tasks, data screening, statistical analysis, and also provide a brief introduction to R programming.

Review of emerging quantitative methodological advances relevant to educational research for which formal course title and syllabus have not been developed and formalized in the UM Bulletin. Allow for experimental instructional formats. See Course Notes for specific topic.

Earning a degree isn’t easy, especially when you have a family and a full-time career. However, enrolling in a data analytics program online provides the flexibility you need. It will allow you to better manage your personal life, career, and education.

It’s a short four-course program that can easily fit into your schedule. Commute time is not only non-existent, you get to set your own pace and use the seven weeks allotted to complete each course. This flexibility allows you to set aside the time you need to review the coursework, study, and complete assignments.

Pursuing data analytics programs online requires a comprehensive and innovative platform that encourages learning and engagement. The UOnline virtual platform uses the Blackboard Learn course management system. It’s easy to navigate and supports faculty, staff, and students. You can access course materials online at any time, anywhere.

Each instructor designs their courses to complement their hands-on instruction. Many also use Zoom to host virtual office hours, meetings, and/or guest speakers. Students can also keep track of their grades using the platform's grade center. This provides an overview of your current standing so you know what areas you need to improve on and where your strengths shine.

You’ll be a part of one of the best statistical analysis programs with access to top-notch instructors. The University’s online platform also facilitates the completion of your certificate in statistics online at your own pace. Although classes aren’t scheduled or live, regular checkpoints ensure students stay on target to achieve course milestones and program completion.

No matter what’s going on in your personal or professional life, you won’t need to miss important course information. Simply retrieve the course information and watch lectures at a time that works for you. The reading materials will also supplement your learning, making it easier to grasp concepts and gain a deep understanding of data. Online degree programs create the perfect learning environment for any student, allowing you to earn your degree your way.

You’ll also have the full support of the University’s faculty and staff. They’ll assist with course content and materials during weekly office hours. You’ll also have access to various student support resources, including a 24/7 IT team for technical issues and a dedicated online advisor.