Drexel University 4 credits BST
The objective of this course is to introduce students to linear regression models (computation, theoretical properties, model interpretation and application). Topics include: Review of basic concepts of matrix algebra that are particularly useful in linear regression, and basic R programing features; (weighted) least square estimation, inference and testing; regression diagnostics, outlier influence; and variable selection and robust regression. Knowledge of calculus 1, calculus 2, and linear algebra required.
Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β written from scratch to your course requirements.
Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.
Expert guides on essay writing, citation styles, study skills, and academic success.
View All Articles
Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
Learn how to cite sources in a research paper using APA, MLA, and Chicago styles, with in-text citation examples and reference-list tips.