PROBABLY CORRECT: HOW TO THINK WITH STATISTICS AND DATA

STAT 602

Provides a thorough grounding in modern statistical methods. The specific learning outcomes for the course are to understand data collection in context (how/why data were collected, key questions under study); explore data by effective graphical and numerical summaries; understand probability concepts and models as tools for studying random phenomena and for statistical inference; analyze data using appropriate, modern statistical models, methods, and software; understand the statistical concepts underlying methods; develop the ability to interpret results and critically evaluate the methods used; communicate data analysis and key findings in context.

EDPSYCH 971

Discuss a different current article from the educational statistics and measurement literature. Explore a variety of subjects in which one might like to eventually conduct research.

EDPSYCH 360

Examines the practice of data science in educational contexts, examining how we draw meaning and make decisions on the basis of data related to students, teaching, formal education systems, and informal learning environments. Focuses on developing fundamental skills for actively working with and interpreting educational data related to students, teaching, formal education systems, and informational learning environments., including: transforming, combining, and effectively summarizing data; creating meaningful graphical representations of data; creating formal models based on data; and communicating findings from data analysis. Develop skills by writing computer code to create reproducible data analysis reports. After introducing foundational data science skills, work through a series of real-world case studies that provide an opportunity to practice, expand, and further refine the skills and to make connections to subject-matter knowledge in the context of education.

EDPSYCH 505

Logic and methods of statistics used in the field of learning analytics. Emphasizes concepts and application rather than computational details to build fundamentals in the areas of inferential statistics. Reliability and validity, scalability, and the implications of inference in applied statistical methodology.

EDPSYCH 760

Introductory descriptive statistics and statistical inference; measures of central tendency and variability, confidence intervals, theory of hypothesis testing, correlation techniques.