Generic Work

A Geometric Approach to Multicollinearity Public Deposited

Downloadable Content

Download PDF

Instructors teaching empirical techniques in managerial economics or economic and business statistics courses often face a dilemma. The typical student in these classes has less mathematical sophistication than those in advanced elective econometrics classes. In courses where students are expected to run regressions and interpret the results, students are often exposed to mathematical topics that are at the edge of their mathematical understanding. The following is the link to the Multicollinearity.xlsx Excel file for the article:  https://www.google.com/search?cx=000646084835614911755:gn97k5nedwc&q=erfle/ExcelGraphics/Multicollinearity.xlsx&tbm=isch&source=univ&client=ms-google-coop&sa=X&ved=2ahUKEwio_6r__DjAhXHhOAKHUb_BEkQsAR6BAgFEAE&biw=1536&bih=750

Erfle, Stephen. "A Geometric Approach to Multicollinearity." The Journal of Economic Education 50, no. 2 (2019): 213.  https://www.tandfonline.com/doi/full/10.1080/00220485.2019.1582385

For more information on the published version, visit Taylor and Francis's Website.


MLA citation style

Erfle, Stephen E. A Geometric Approach to Multicollinearity. . 2019. https://dickinson.hykucommons.org/concern/generic_works/dcf6a757-77db-4ef7-8fa0-bbf10115d843?locale=en

APA citation style

Erfle, Stephen E. (2019). A Geometric Approach to Multicollinearity. https://dickinson.hykucommons.org/concern/generic_works/dcf6a757-77db-4ef7-8fa0-bbf10115d843?locale=en

Chicago citation style

Erfle, Stephen E. A Geometric Approach to Multicollinearity. 2019. https://dickinson.hykucommons.org/concern/generic_works/dcf6a757-77db-4ef7-8fa0-bbf10115d843?locale=en

Note: These citations are programmatically generated and may be incomplete.

Items