Throughout the course, you have studied and used tools and techniques that have underlying statistical theory and assumptions. Regression is no different. Haphazard application of regression analysis, as with any type of statistical technique, can lead to results that are inaccurate and that, even worse, can get you or your employer into trouble (whether that trouble involves product faults, legal issues, or simply wasted time and money). Thus, you must always be cognizant of the conditions of the problem as they relate to the assumptions and theory associated with your application of regression techniques.
Regression analysis is a statistical procedure, and it requires that certain assumptions be satisfied if you are to correctly interpret the results. What are the assumptions of regression, and how can these assumptions be checked? Which assumptions, if violated, can cause the greatest bias in the results of the regression analysis? Why? You may draw on any book, article, website, or other reliable resource in answering this question.
Be sure to defend and support your opinion and remember to properly cite your sources according to APA guidelines.
Testimonials
